Computer science Books

Book SynopsisHow did we end up here, masters of scientific insight, purveyors of ever more powerful technologies, astride the burning planet that created us, and now responsible for cleaning up the mess and determining the future direction of all of life? And what do we do about it?Technology is Dead is a book that attempts to answer both of those questions. It is a book of both challenge and hope, written for those who are able or willing to lead us out of our global predicament. It is a book for everybody: the politicians, CEOs, community leaders, everyday parents, and young people who understand that we must change our ways to ensure a sustainable future for all living things and the planet we rely on.

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Book SynopsisReflecting the immense progress in the development and use of software metrics in the past decades, this third edition provides an up-to-date, accessible, and comprehensive introduction to software metrics. This edition contains new material relevant to object-oriented design, design patterns, model-driven development, and agile development procTrade Review"The wait for a new edition of this book is over. Long considered the go-to text for its thorough coverage of software measurement and experimentation, the new edition succeeds splendidly in bringing the field up to date while including new and important topics. … updated with the latest results from recent advances in software measurement research and practice. … The authors do an outstanding job of balancing formal analysis topics with examples that ground the reader in practical application. … Both researchers and practitioners alike will gain a valuable understanding of why measurement is critical for quality improvements in software development processes and software products. … With this updated edition, this book solidifies its standing as the most complete reference text for software measurement."—Computing Review, April 2015"I have been using this book as my primary reference on software metrics for over 20 years now. It still remains the best book by far on the science and practice of software metrics. This latest edition has some important updates, especially with the inclusion of material on Bayesian networks for prediction and risk assessment."—Paul Krause, University of Surrey, Guildford, UK"Great introduction to software metrics, measurement, and experimentation. This will be a must-read for my software engineering students."—Lukasz Radlinski, PhD, West Pomeranian University of Technology, Szczecin, Poland"I have loved this book from the first edition and with each new edition it just keeps getting better and better. I use this book constantly in my software engineering research and always recommend it to students. It is so much more than a software metrics book; to me it is an essential companion to rigorous empirical software engineering."—Dr. Tracy Hall, Department of Computer Science, Brunel University, Uxbridge, UK"This new edition of Software Metrics succeeds admirably in bringing the field of software measurement up to date and in delivering a wider range of topics to its readers as compared to its previous edition. I have both reviewed and used the book in my software measurement courses and find it to be one of the most advanced and well structured on the market today, tailored for training software engineers in both theoretical and practical aspects of software measurement. I look forward to continuing the use of the book for teaching purposes and am very comfortable offering my recommendation for this book as a primary textbook for graduate or undergraduate courses on software measurement. Thank you again for providing such a quality book to our software engineering education programs."—Olga Ormandjieva, Associate Professor, Department of Computer Science and Software Engineering, Concordia University, Canada"This book lucidly and diligently covers the nuts and bolts of software measurement. It is an excellent reference on software metric fundamentals, suitable as a comprehensive textbook for software engineering students and as a definitive manual for industry practitioners."—Mohammad Alshayeb, Associate Professor of Software Engineering, King Fahd University of Petroleum and MineralsTable of ContentsFundamentals of Measurement and Experimentation: Measurement: What Is It and Why Do It? The Basics of Measurement. A Goal-Based Framework for Software Measurement. Empirical Investigation. Software Metrics Data Collection. Analyzing Software Measurement Data. Metrics for Decision Support: The Need for Causal Models. Software Engineering Measurement: Measuring Internal Product Attributes: Size. Measuring Internal Product Attributes: Structure. Measuring External Product Attributes. Software Reliability: Measurement and Prediction. Appendix. Bibliography. Index.

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Book SynopsisThe ability to use computers to solve mathematical relationships is a fundamental skill for anyone planning for a career in science or engineering. For this reason, numerical analysis is part of the core curriculum for just about every undergraduate physics and engineering department. But for most physics and engineering students, practical programming is a self-taught process.This book introduces the reader not only to the mathematical foundation but also to the programming paradigms encountered in modern hybrid software-hardware scientific computing. After completing the text, the reader will be well-versed in the use of different numerical techniques, programming languages, and hardware architectures, and will be able to select the appropriate software and hardware tool for their analysis.It can serve as a textbook for undergraduate courses on numerical analysis and scientific computing courses within engineering and physical sciences departments. It will also be a valuable guidebook for researchers with experimental backgrounds interested in working with numerical simulations, or to any new personnel working in scientific computing or data analysis.Key Features: Includes examples of solving numerical problems in multiple programming languages, including MATLAB, Python, Fortran, C++, Arduino, Javascript, and Verilog Provides an introduction to modern high-performance computing technologies including multithreading, distributed computing, GPUs, microcontrollers, FPGAs, and web cloud computing Contains an overview of numerical techniques not found in other introductory texts including particle methods, finite volume and finite element methods, Vlasov solvers, and molecular dynamics A video of the author discussing the book can be accessed here: https://www.youtube.com/watch?v=KYn8aDKXlcs

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Book SynopsisThe emerging field of Data Science has had a large impact on science and society. This book explores how one distinguishing feature of Data Science its focus on data collected from social and environmental contexts within which learners often find themselves deeply embedded suggests serious implications for learning and education.Drawing from theories of learning and identity development in the learning sciences, this volume investigates the impacts of these complex relationships on how learners think about, use, and share data, including their understandings of data in light of history, race, geography, and politics. More than just using real world examples' to motivate students to work with data, this book demonstrates how learners' relationships to data shape how they approach those data with agency, as part of their social and cultural lives. Together, the contributions offer a vision of how the learning sciences can contribute to a more expansive, socially awareTable of Contents1. Introduction: Situating Data Science—Exploring How Relationships to Data Shape Learning 2. At Home with Data: Family Engagements with Data Involved in Type 1 Diabetes Management 3. Examining Spontaneous Perspective Taking and Fluid Self-to-Data Relationships in Informal Open-Ended Data Exploration 4. Learning at the Intersection of Self and Society: The Family Geobiography as a Context for Data Science Education 5. Authoring Data Stories in a Media Makerspace: Adolescents Developing Critical Data Literacies 6. From Data Collectors to Data Producers: Shifting Students’ Relationship to Data, Lisa Hardy 7. Scripts and Counterscripts in Community-Based Data Science: Participatory Digital Mapping and the Pursuit of a Third Space 8. Learning to Reason with Data: How Did We Get Here and What Do We Know? 9. Educating Data Scientists and Data Literate Citizens for a New Generation of Data

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Book SynopsisProvides tips for using servers and places to seek resources to find out about what's going on in the bioinformatics world. This book helps you: analyze all types of sequences; use all types of databases; work with DNA and protein sequences; conduct similarity searches; build a multiple sequence alignment; and edit and publish alignments.Table of ContentsIntroduction. Part I: Getting Started in Bioinformatics. Chapter 1: Finding Out What Bioinformatics Can Do for You. Chapter 2: How Most People Use Bioinformatics. Part II: A Survival Guide to Bioinformatics. Chapter 3: Using Nucleotide Sequence Databases. Chapter 4: Using Protein and Specialized Sequence Databases. Chapter 5: Working with a Single DNA Sequence. Chapter 6: Working with a Single Protein Sequence. Part III: Becoming a Pro in Sequence Analysis. Chapter 7: Similarity Searches on Sequence Databases. Chapter 8: Comparing Two Sequences. Chapter 9: Building a Multiple Sequence Alignment. Chapter 10: Editing and Publishing Alignments. Part IV: Becoming a Specialist: Advanced Bioinformatics Techniques. Chapter 11: Working with Protein 3-D Structures. Chapter 12: Working with RNA. Chapter 13: Building Phylogenetic Trees. Part V: The Part of Tens. Chapter 14: The Ten (Okay, Twelve) Commandments for Using Servers. Chapter 15: Some Useful Bioinformatics Resources. Index.

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Book SynopsisWritten in partnership with SAP, this is the first IS book that provides the right introductory content and combines it with hands-on practice in the form of a simulated SAP environment. It also offers a unique perspective by discussing both the typical processes in organizations and the role of information systems in supporting these processes.Table of ContentsChapter 1: Organizations, Processes, and Information Systems. Chapter 2: Enterprise Systems. Chapter 3: The Procurement Process. Chapter 4: The Fulfillment Process. Chapter 5: The Production Process. Chapter 6: Integrated Processes.

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Book SynopsisBringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. The second edition of this introductory book features several new codes and 140 new problems (many on physics applications), as well as new sections on the singular-value decomposition, derivative-free optimization, Bayesian linear regression, neural networks, and partial differential equations. The last section in each chapter is an in-depth project, tackling physics problems that cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the numerical methods often used in the subject.Trade Review'A fantastic addition as an introductory textbook for computational physics. The book is timely, and the author made thoughtful and, in my view, many wise choices. The book is comprehensive and yet accessible to undergraduate students.' Shiwei Zhang, the Flatiron Institute and the College of William & Mary'Gezerlis' book Numerical Methods in Physics with Python is a beautiful example of how an established subject can be brought to the next level by making it very accessible and by introducing several insightful and interdisciplinary applications. This second edition considerably extends the set of exercises, resulting in an extremely useful resource for both students and teachers. Strongly recommended!' Sonia Bacca, Johannes Gutenberg-Universität Mainz'This new edition of Numerical Methods… is another great example of Gezerlis' passion for teaching and for doing so carefully and precisely. Especially welcome, in my view, are the addition of problems at the end of each chapter and the discussion of singular value decomposition (SVD) and Bayesian methods. The SVD is one of the crown jewels of linear algebra which modern students interested in machine learning will surely find beneficial. To physics, computer science, or engineering students mesmerized by the fast Fourier transform, Gezerlis' excellent explanation of it in Chapter 6 is likely to shed some light on the underlying divide-and-conquer algorithm, which is an essential classic.' Joaquin Drut, University of North Carolina at Chapel HillPraise for the first edition: 'I enthusiastically recommend Numerical Methods in Physics with Python by Professor Gezerlis to any advanced undergraduate or graduate student who would like to acquire a solid understanding of the basic numerical methods used in physics. The methods are demonstrated with Python, a relatively compact, accessible computer language, allowing the reader to focus on understanding how the methods work rather than on how to program them. Each chapter offers a self-contained, clear, and engaging presentation of the relevant numerical methods, and captivates the reader with well-motivated physics examples and interesting physics projects. Written by a leading expert in computational physics, this outstanding textbook is unique in that it focuses on teaching basic numerical methods while also including a number of modern numerical techniques that are usually not covered in computational physics textbooks.' Yoram Alhassid, Yale University'In Numerical Methods in Physics with Python by Gezerlis, one finds a resource that has been sorely missing! As the usage of Python has become widespread, it is too often the case that students take libraries, functions, and codes and apply them without a solid understanding of what is truly being done 'under the hood' and why. Gezerlis' book fills this gap with clarity and rigor by covering a broad number of topics relevant for physics, describing the underlying techniques, and implementing them in detail. It should be an important resource for anyone applying numerical techniques to study physics.' Luis Lehner, Perimeter Institute for Theoretical Physics'Gezerlis' text takes a venerable subject - numerical techniques in physics - and brings it up to date and makes it accessible to modern undergraduate curricula through a popular, open-source programming language. Although the focus remains squarely on numerical techniques, each new lesson is motivated by topics commonly encountered in physics and concludes with a practical hands-on project to help cement the students' understanding. The net result is a textbook which fills an important and unique niche in pedagogy and scope, as well as a valuable reference for advanced students and practicing scientists.' Brian Metzger, Columbia UniversityTable of ContentsPreface; 1. Idiomatic Python; 2. Numbers; 3. Derivatives; 4. Matrices; 5. Zeroes and minima; 6. Approximation; 7. Integrals; 8. Differential equations; Appendix A. Installation and setup; Appendix B. Number representations; Appendix C. Math background; Bibliography; Index.

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Book SynopsisThis is the first self-contained introduction to the use of string diagrams to reason in elementary category theory. Written in an informal expository style, it features hundreds of carefully chosen diagrams to aid understanding. With numerous worked examples and exercises, the text is ideal for graduate students and advanced undergraduates.Trade Review'String diagrams have proven an indispensable tool in modern category theory, enabling intuitive graphical reasoning while doing away with much of the bookkeeping that tends to bog down equational arguments. This textbook introduces category theory by way of string diagrams, making it an excellent choice both for beginners in category theory, as well as for more experienced category theorists seeking to add string diagrammatic reasoning to their repertoire.' Robin Kaarsgaard, University of Edinburgh'Well-chosen notation plays a vital role in constructive calculation because it facilitates the exploitation of algebraic properties. This book's exemplary use of string diagrams in category theory will inspire and invigorate the calculational method. Peruse and ponder its colourful beauty.' Roland Backhouse, University of NottinghamTable of ContentsPrologue; 1. Category theory; 2. String diagrams; 3. Monads; 4. Adjunctions; 5. Putting it all together; Epilogue; Appendix. Notation; References; Index.

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Book SynopsisThis book offers a practical approach to understanding, designing, and building sound software based on solid principles. Using a unique Q&A format, this book addresses the issues that engineers need to understand in order to successfully work with software engineers, develop specifications for quality software, and learn the basics of the most common programming languages, development approaches, and paradigms. The new edition is thoroughly updated to improve the pedagogical flow and emphasize new software engineering processes, practices, and tools that have emerged in every software engineering area.Features: Defines concepts and processes of software and software development, such as agile processes, requirements engineering, and software architecture, design, and construction. Uncovers and answers various misconceptions about the software development process and presents an up-to-date reflection on the state of practice in the indusTable of ContentsIntroduction, 1. The Profession of Software Engineering, 2. Software Properties, Processes, and Standards, 3. Software Requirements Engineering, 4. Software Architecture, 5. Designing Software, 6. Software Construction, 7. Software Quality Assurance, 8. Managing Software Projects and Software Engineers, 9. Software Engineering: Roadmap to the Future

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Book SynopsisIn Joyful Infographics: A Friendly, Human Approach to Data, one of the leading graphic designers of recent times shows how a judicious use of humor can make infographics more understandable. Written in non-academic, easy-to-understand language, and with historical and contemporary visual examples presented throughout, this small book provides a short history of light-hearted graphics. The text outlines nine clear ways to make graphics more understandable, explores the importance of the audience, shows you how to make information come alive during presentations through live-action performance' graphics, discusses why joy and smiling are good for you, and shows you how not to overdo it. The author website, featuring enlargeable graphics, can be found here: https://www.joyfulinfographics.com/.Even if a subject is delicate, controversial, or taboo, being graphically friendly to the audience is the right way to eTrade Review"This glorious project positions the word muse in the larger word amusing. Nigel’s modesty and the extent of the publications and innovations that he has brought uniquely to the profession of graphic design, information design, information architecture, explanation design and illustration is certainly enough to put him in the pantheon of the finest graphic designers of the late 20th and now the 21st century. He is one of my muses."-Richard Saul Wurman, Architect, Graphic Designer, Author, and Founder of TED"This is essential reading for information professionals, academics and students. Arguments about the way that information should be presented have been going on for decades. This subject resonates with anyone in the field, professional or academic. When presenting information, the balance between a serious approach and a lighter one is always a factor. It is all about engaging the intended audience. "-John Grimwade, School of Visual Communication, Ohio University, USA"Nigel Holmes has helped shape the standards of modern infographics like no other. His infographics are easily accessible, well-structured and - of course - fact-based. Nigel's body of work spans all types of infographics: charts, factual representations, and maps. They are memorized quickly and their information can be remembered accurately: this is mainly because they are designed to be light-hearted, humorous and confident. How Nigel plans, develops and designs infographics is a lesson par excellence. That's why Nigel Holmes' infographic work is not only required reading for my students: Understanding Nigel's approach to infographic design and his infographics' internal structure must be understood by my students in order to pass the course. This book will be in our library."-Michael Stoll, Augsburg University of Applied Sciences, Germany"Nigel’s fantastic work feeds the need to learn from the past in order to create more work like this today. It is a fantastic guide that informs as much as it entertains."-Jason Forrest, Editor-in-Chief, Nightingale: the journal of the Data Visualization Society"One of the best things with Nigel’s graphics is his approach, the stories are always smart and contemporary, with a good balance of information and humor. Readers will be inspired to read information in this positive way." -Fernando Gomez Baptista, National Geographic"Few things are as important for designers now as being able to effectively translate big data into memorable, meaningful, and concise graphics. Nigel Holmes has spent decades fostering human connection and understanding through joyful infographics. In this book, he applies his world-renowned brainy and playful approach to teach the next generation of graphic communicators how to master his craft."-Amanda Hostalka, Dean, School of Design, Stevenson University, USA"I am a huge fan of Nigel Holmes’ ability to infuse joy and humanity into science graphics. He even managed to inject life into an explanatory diagram about group theory and the mathematical underpinnings of symmetry, providing brilliant design details that acted as a welcoming gesture for folks new to the topic."-Jen Christiansen, senior graphics editor, Scientific American"Sign and symbol languages appear to be enjoying a 21st century renaissance as part of the expanding universe of digital data visualization. New ways of presenting the floods of data on literally everything has made it necessary to increase data literacy. What better way than through humor? Who better than the data viz pioneer, Nigel Holmes?" -Steven Heller, Author, co-chair MFA Design, School of Visual Arts, USA"Nigel Holmes is terrific."–Tim Harford, Author, Senior Columnist, Financial Times“Joyful Infographics itself is as friendly as Holmes’s graphic design work. The book is filled with examples of imaginative infographics. And he draws from a wide range of examples; readers can study visuals from fields as diverse as human physiology, advertising, and the Olympic games. Holmes also grounds his work in history: Chapter 3 traces visual representations of information throughout history, referencing everything from the Chauvet cave paintings to Henry Beck’s Tube maps, from the Bayeux Tapestry to emojis. Holmes also provides actionable instructions for designers. Chapter 4 offers nine techniques to make infographics more engaging, and Chapter 9 warns “Don’t do this!” and provides examples of how not to design infographics. Following his guidelines will help designers keep the humanity in their visual communication. In a time when many communication professionals are wondering how much of our work artificial intelligence can do, it’s a good reminder that it takes the human touch to communicate data in a way that audiences want to engage with.”--Elizabeth Hardin, University of Alabama, USA, Technical Communication, Volume 70, Number 3, August 2023Table of Contents0. Warming up : It's good to exercise. 1. Introduction: in which I try to define Joyful and Infographics. 2. Influences : Great Uncle George, Monty Python, Eadweard Muybridge, Thelonious Monk (among others). 3. Pictorail data through the ages. 4. Nine ways to make your graphics joyful : A timeline. 5. Icons. 6. Joyful presentations: Speak up. 7. Science : Serious fun for all. 8. Chartoons and jokes : Including a chart about diamonds. 9. Don't do this! : Really awful things I've done that you really shouldn't.

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Book SynopsisNumerical simulation models are used in all engineering disciplines for modeling physical phenomena to learn how the phenomena work, and to identify problems and optimize behavior. Smart Proxy Models provide an opportunity to replicate numerical simulations with very high accuracy and can be run on a laptop within a few minutes, thereby simplifying the use of complex numerical simulations, which can otherwise take tens of hours. This book focuses on Smart Proxy Modeling and provides readers with all the essential details on how to develop Smart Proxy Models using Artificial Intelligence and Machine Learning, as well as how it may be used in real-world cases. Covers replication of highly accurate numerical simulations using Artificial Intelligence and Machine Learning Details application in reservoir simulation and modeling and computational fluid dynamics Includes real case studies based on commercially available simulators Table of Contents 1. Artificial Intelligence and Machine Learning. 2. Numerical simulation and modeling. 3. Proxy modeling. 4. Smart Proxy Modeling for numerical reservoir simulation. 5. Smart Proxy Modeling for computational fluid dynamics (CFD).

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Book SynopsisThis book presents a contextualized overview of the history of Chinese animated film, pointing out the most influential self-definitions of Chinese culture employed in animation art of Mao Zedong's rule (19491976) but largely focusing on the representation strategies created in the times of reforms and opening-up under Deng Xiaoping (19781989/1992).Deeply grounded in cultural studies, the book employs an interdisciplinary approach, interlacing the reflection with the perspectives of political science, film studies, and film festival studies. It focuses on phenomena anchored to the paradigms of nationalization, reform, and internationalization: among them, nuanced understanding of the minzu (national) category (including the classic style of Chinese animation); invention of wash-and-ink painting animation (shuimo donghua); renewal of film theory and animated film language; soft power and cultural diplomacy; and regular access and co-creation of the internatioTable of Contents1. Nationalization of Animation 2. Animation Reformed 3. Sino-European Opening-Up in the Area of Art-House Animation

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Book SynopsisWith this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the different types of analysis commonly conducted with big data, this accessible reference presents clear-cut explanations of the general workings of big data tools. Instead of spending time on HOW to install specific packages, it focuses on the reasons WHY readers would install a given package.The book provides authoritative guidance on a range of tools, including open source and proprietary systems. It details the strengths and weaknesses of incorporating big data analysis into decision-making and explains how to leverage the strengths while mitigating the weaknesses. Describes the benefits of distrTable of ContentsIntroduction. The Mother of Invention’s Triplets: Moore’s Law, the Proliferation of Data, and Data Storage Technology. Hadoop. HBase and Other Big Data Databases. Machine Learning. Statistics. Google. Geographic Information Systems. Discovery. Data Quality. Benefits. Concerns.

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Book SynopsisA bestseller in its French edition, this book is original in its construction and its success in the French market demonstrates its appeal. It is based on three principles: (1) An organization of the chapters by families of algorithms: exhaustive search, divide and conquer, etc. On the contrary, there is no chapter devoted only to a systematic exposure of, say, algorithms on strings. Some of these will be found in different chapters. (2) For each family of algorithms, an introduction is given to the mathematical principles and the issues of a rigorous design, with one or two pedagogical examples. (3) For the most part, the book details 150 problems, spanning seven families of algorithms. For each problem, a precise and progressive statement is given. More importantly, a complete solution is detailed, with respect to the design principles that have been presented; often, some classical errors are pointed out. Roughly speaking, two-thirds of the book is devoted to the detailed rational cTable of ContentsTable of ContentsPreface Mathematics and Computer Science: Some Useful Notions Complexity of an Algorithm Specifications, Invariants, Iteration Reduce and Conquer, Recursion Generate and Test Branch and Bound Greedy Algorithms Divide and Conquer Dynamic Programming NotationsList of ProblemsBibliographyIndex

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Book SynopsisBlenderTM is a free Open-Source 3D Computer Modeling and Animation Suite incorporating Character Rigging, Particles, Real World Physics Simulation, Sculpting, Video Editing with Motion Tracking and 2D Animation within the 3D Environment.Blenderis FREE to download and use by anyone for anything.The Complete Guide to Blender Graphics: Computer Modeling and Animation, Eighth Edition is a unified manual describing the operation of the program, updated with reference to the Graphical User Interface for Blender Version 3.2.2, including additional material covering Blender Assets, Geometry Nodes, and Non-Linear Animation.Divided into a two-volume set, the book introduces the program's Graphical User Interface and shows how toTable of ContentsIntroduction. The Author. Preamble. CH01 Objects in the 3D View Editor. CH02 Editing & Add-Ons. CH03 Editing with Generate Modifiers. CH04 Editing with Deform Modifiers. CH05 Editing Using Curves. CH06 Material Assignment. CH07 Rendering. CH08 Animation. CH09 Constraints. CH10 Armatures & Character Rigging. CH11 Shape Keys & Action Editors. CH12 Particle Systems. CH13 Physics and Simulation. CH14 Dynamic Paint. CH15 Geometry Nodes. CH16 Drivers. Ch17 Non Linear Animation. CH18 Rigging – Rigify – Animbox. CH19 Blender Render Engines. Index.

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Book SynopsisBlenderTM is a free Open-Source 3D Computer Modeling and Animation Suite incorporating Character Rigging, Particles, Real World Physics Simulation, Sculpting, Video Editing with Motion Tracking and 2D Animation within the 3D Environment.Blender is FREE to download and use by anyone for anything.The Complete Guide to Blender Graphics: Computer Modeling and Animation, Eighth Edition is a unified manual describing the operation of the program, updated with reference to the Graphical User Interface for Blender Version 3.2.2, including additional material covering Blender Assets, Geometry Nodes, and Non-Linear Animation.Divided into a two-volume set, the book introduces the program's Graphical User Interface and shows howTable of ContentsIntroduction. Download and Installation. The Author. Preamble. CH01 Understanding the Interface. CH02 Editors-Workspaces-Themes. CH03 Navigate and Save. CH04 Objects in the 3D View Editor. CH05 Editing Objects. CH06 Editing Tools. CH07 Editing with Modifiers. CH08 Editing Techniques- Examples. CH09 Materials- Textures- Nodes. CH10 Textures. CH11 Node Systems and Usage. CH12 Scene Lighting & Cameras. CH13 Viewport Shading. CH14 Rendering. CH15 Animation. CH16 Armatures & Character Rigging. CH17 3D Text. CH18 Blender Assets. CH19 Making a Movie. CH20 The Outliner and Collections. Index.

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Book SynopsisThis edited collection reflects contemporary challenges faced by police forces across the globe and the role of technology in addressing them. The use of science and technology raises questions about ethics, training, the well-being of people, and freedom. New technologies promise to foster police practices based on intelligence, accuracy, and preparedness, and are considered necessary to overcome challenges such as declining budgets, lack of personnel, and legitimacy. However, technologies can also be used for authoritarian and nefarious purposes. For those reasons, this book aims to discuss related topics from various contexts to establish connections among common problems in the field of policing across the globe. This book provides an internationally relevant assessment of the use of technology in the field of policing, as well as the impact on training and police well-being. It is ideal for an academic audience at both graduate and undergraduate leve

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Book SynopsisThe WebGPU Sourcebook: High-Performance Graphics and Machine Learning in the Browser explains how to code web applications that access the clientâs graphics processor unit, or GPU. This makes it possible to render graphics in a browser at high speed and perform computationally intensive tasks such as machine learning. By taking advantage of WebGPU, web developers can harness the same performance available to desktop developers.The first part of the book introduces WebGPU at a high level, without graphics theory or heavy math. The chapters in the second part are focused on graphical rendering and the rest of the book focuses on compute shaders.This book walks through several examples of WebGPU usage. It also: Discusses the classes and functions defined in the WebGPU API and shows how theyâre used in practice Explains the theory of graphical rendering and shows how to implement rendering inside a web application Examines the theory

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Book SynopsisTake the next step in raising your coding skills and dive into the intricacies of Java Standard Libraries. You will continue to raise your coding skills, and test your Java knowledge on tricky programming tasks, with the help of the pirate Captain CiaoCiao. This is the second of two volumes which provide you with everything you need to excel in your Java journey, including tricks that you should know in detail as a professional, as well as intensive training for clean code and thoughtful design that carries even complex software.Features: 149 tasks with commented solutions on different levels For all paradigms: object-oriented, imperative, and functional Clean code, reading foreign code, and object-oriented modeling With numerous best practices and extensively commented solutions to the tasks, these books provide the perfect workout for professional software development with Java.

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Book SynopsisBy using test-driven development (TDD), you'll write code that's easy to understand, retains its elegance, and works for months, even years, to come. With this indispensable guide, you'll learn how to use TDD with three different languages: Go, JavaScript, and Python.

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Book SynopsisWritten for the WJEC/Eduqas A/AS Level Computer Science specifications for first teaching from 2015, this print student book and Digital Student Book help students build their knowledge and master underlying computing principles and concepts. The resource develops computational thinking, programming and problem-solving skills. Suitable for all abilities, it puts computing into context and gives students a real-life view on professional applications of computing skills. Digital Student Books contain rich digital content such as animated tutorials. Answers to end-of-chapter questions are located in the free online teacher''s resource.

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Book SynopsisLearning to program isn''t just learning the details of a programming language: to become a good programmer you have to become expert at debugging, testing, writing clear code and generally unsticking yourself when you get stuck, while to do well in a programming course you have to learn to score highly in coursework and exams. Featuring tips, stories and explanations of key terms, this book teaches these skills explicitly. Examples in Python, Java and Haskell are included, helping you to gain transferable programming skills whichever language you are learning. Intended for students in Higher or Further Education studying early programming courses, it will help you succeed in, and get the most out of, your course, and support you in developing the software engineering habits that lead to good programs.Trade Review'Perdita Stevens' book How to Write Good Programs provides a wealth of excellent advice tailored to beginning students of programming. It is language-agnostic, well structured, and delivered in an accessible manner. It might as well have the words 'Don't Panic' in large, friendly letters on the cover.' Jeremy Gibbons, University of Oxford'This is the book I wish had existed during my time at university and at the beginning of my career! It explains fundamental concepts independently of a concrete programming language and contains many practical observations and tips to overcome situations where novice programmers tend to get stuck.' Jennifer Tenzer, Senior Developer'This is a unique book that feels like a conversation over a coffee with an experienced expert in computer programing. It is full of practical tips, insights, and folklore that will be of great benefit to anyone who wants to learn how to program well.' Professor Tom Ward, University of Leeds'Stevens's book differs from other coding books in that it assumes minimal knowledge in its readers. She discusses the concept of 'program', clarifying which problem you want to solve and choosing a development environment, all before she gets to her concrete coding tips. Especially the chapter on how to fix mistakes is a boon to the novice programmer. Few things are as frustrating as accidentally throwing away working code or - worse - not being able to get your program back to working order. And for those who have finally mastered programming fairly well, but have difficulty with their schoolwork, Stevens concludes with two chapters on how to score well on homework assignments and exams.' Karl van Heijster, De Leesclub van AllesTable of Contents1. Introduction; 2. What Are Good Programs?; 3. How to Get Started; 4. How to Understand Your Language; 5. How to Use the Best Tools; 6. How to Make Sure You Don't Lose Your Program; 7. How to Test Your Program; 8. How to Make Your Program Clear; 9. How to Debug Your Program; 10. How to Improve Your Program; 11. How to Get Help (without Cheating); 12. How to Score Well in Coursework; 13. How to Score Well in a Programming Exam; 14. How to Choose a Programming Language; 15. How to Go Beyond This Book; References; Index.

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Book SynopsisHow to make customers feel good about doing what you want Learn how companies make us feel good about doing what they want. Approaching persuasive design from the dark side, this book melds psychology, marketing, and design concepts to show why we re susceptible to certain persuasive techniques.Table of ContentsForeword xi Introduction xiii Evil designs and their virtuous counterparts xiii Pride 1 Misplaced pride causes cognitive dissonance 1 Provide reasons for people to use 3 Social proof: Using messages from friends to make it personal and emotional 5 Dispel doubt by repeating positive messages 7 Personal messages hit home 11 Gain public commitment to a decision 16 Change opinions by emphasizing general similarities 19 Use images of certification and endorsement 22 Closure: The appeal of completeness and desire for order 25 Help people complete a set 26 Pander to people’s desire for order 32 Manipulating pride to change beliefs 35 Sloth 39 Desire lines: From A to B with as few barriers as possible 39 Path of least resistance 41 Reduced options and smart defaults smooth the decision process 44 Provide fewer options 45 Pre-pick your preferred option 50 Make options hard to find or understand 53 Negative options: Don’t not sign up! 56 Sloth: Is it worth the effort? 64 Gluttony 67 Deserving our rewards 67 Make customers work for a reward 69 Consider a small reward rather than a big one 72 Hide the math 75 Show the problems 78 Escalating commitment: foot-in-the-door, door-in-the-face 84 Foot-in-the-door 84 Door-in-the-face 87 Present hard decisions only after investment 90 Invoking gluttony with scarcity and loss aversion 93 The Tom Sawyer effect 93 Instill doubt to prevent cancellations 96 Impatience leads to compliance 99 Self-control: Gluttony’s nemesis 101 Anger 103 Avoiding anger 104 Use humor to deflect anger 104 Avoid overt anger with a slippery slope 107 Use metaphysical arguments to beat opponents 112 Embracing anger 117 Use anonymity to encourage repressed behaviors 119 Give people permission 124 Scare people (if you have the solution) 129 Using anger safely in your products 134 Envy 137 Manufacturing envy through desire and aspiration 138 Create desirability to produce envy 138 Create something aspirational 140 Make people feel ownership before they’ve bought 145 Status envy: demonstrating achievement and importance 150 Create status differences to drive behavior 151 Emphasize achievement as a form of status 154 Encourage payment as an alternative to achievement 156 Let users advertise their status 159 Let people feel important 161 Manufacturing and maintaining envy in your products 166 Lust 169 Creating lust: Using emotion to shape behavior 169 Say “I love you” 170 Be the second best 174 Frame your message as a question 178 Create an in-group 182 Controlling lust: Using desire to get a commitment 185 Give something to get something 186 Make something free 190 Sell the intangible value 195 Make a request in order to be seen more favorably 198 Lustful behavior 201 Greed 203 Learning from casinos: Luck, probability, and partial reinforcement schedules 204 Use a partial reinforcement schedule 208 Make it into a game 211 Customers should “win” rather than “finish” or “buy” 214 Further inflate people’s (already overconfident) feelings of skill and mastery 217 Make rewards seem due to skill, not luck 221 Create a walled garden 225 Anchoring and arbitrary coherence 227 Own the anchor 229 Move from money to tokens 233 Encourage breakage 236 Make it expensive 238 Show your second-best option first 240 Break coherence to justify prices 243 Feeling greedy? 246 Evil by Design 249 Should you feel bad about deception? 250 Should you feel bad about using the principles in this book? 254 Be purposefully persuasive 258 The Persuasive Patterns Game 259 References 269 Index 297

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Book SynopsisThe best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone''s tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the techniTrade ReviewIt is refreshing to read a book whose author simply puts the big data hype into practice. Ultimately, it offers a comprehensive narrative of why and how data is transforming the way businesses operate. (Marginalia on Engagement, April 2016) "This book is a brilliant introduction to the concept of big data, perfect for anybody who would like to know what it's all about and how this can be of benefit." (Institute of Management Services Journal, June 2016) Warmly recommended (The Marketing Society, July 2016) Another excellent text from Marr (BCS, August 2016)Table of ContentsIntroduction 1 1 Walmart: How Big Data is Used to Drive Supermarket Performance 5 2 CERN: Unravelling the Secrets of the Universe With Big Data 11 3 Netflix: How Netflix Used Big Data to Give Us the Programmes We Want 17 4 Rolls-Royce: How Big Data is Used to Drive Success in Manufacturing 25 5 Shell: How Big Oil Uses Big Data 31 6 Apixio: How Big Data is Transforming Healthcare 37 7 Lotus F1 Team: How Big Data is Essential to the Success of Motorsport Teams 45 8 Pendleton & Son Butchers: Big Data For Small Business 51 9 US Olympic Women’s Cycling Team: How Big Data Analytics is Used to Optimize Athletes’ Performance 57 10 ZSL: Big Data in the Zoo and to Protect Animals 63 11 Facebook: How Facebook Use Big Data to Understand Customers 69 12 John Deere: How Big Data Can Be Applied On Farms 75 13 Royal Bank of Scotland: Using Big Data to Make Customer Service More Personal 81 14 LinkedIn: How Big Data is Used to Fuel Social Media Success 87 15 Microsoft: Bringing Big Data to the Masses 95 16 Acxiom: Fuelling Marketing With Big Data 103 17 US Immigration and Customs: How Big Data is Used to Keep Passengers Safe and Prevent Terrorism 111 18 Nest: Bringing the Internet of Things Into the Home 117 19 GE: How Big Data is Fuelling the Industrial Internet 125 20 Etsy: How Big Data is Used in a Crafty Way 131 21 Narrative Science: How Big Data is Used to Tell Stories 137 22 BBC: How Big Data is Used in the Media 143 23 Milton Keynes: How Big Data is Used to Create Smarter Cities 149 24 Palantir: How Big Data is Used to Help the CIA and to Detect Bombs in Afghanistan 157 25 Airbnb: How Big Data is Used to Disrupt the Hospitality Industry 163 26 Sprint: Profiling Audiences Using Mobile Network Data 169 27 Dickey’s Barbecue Pit: How Big Data is Used to Gain Performance Insights Into One of America’s Most Successful Restaurant Chains 175 28 Caesars: Big Data at the Casino 181 29 Fitbit: Big Data in the Personal Fitness Arena 189 30 Ralph Lauren: Big Data in the Fashion Industry 195 31 Zynga: Big Data in the Gaming Industry 199 32 Autodesk: How Big Data is Transforming the Software Industry 205 33 Walt Disney Parks and Resorts: How Big Data is Transforming Our Family Holidays 211 34 Experian: Using Big Data to Make Lending Decisions and to Crack Down On Identity Fraud 217 35 Transport for London: How Big Data is Used to Improve and Manage Public Transport in London 223 36 The US Government: Using Big Data to Run a Country 229 37 IBM Watson: Teaching Computers to Understand and Learn 237 38 Google: How Big Data is at the Heart of Google’s Business Model 243 39 Terra Seismic: Using Big Data to Predict Earthquakes 251 40 Apple: How Big Data is at the Centre of Their Business 255 41 Twitter: How Twitter and IBM Deliver Customer Insights From Big Data 261 42 Uber: How Big Data is at the Centre of Uber’s Transportation Business 267 43 Electronic Arts: Big Data in Video Gaming 273 44 Kaggle: Crowdsourcing Your Data Scientist 281 45 Amazon: How Predictive Analytics Are Used to Get a 360-Degree View of Consumers 287 Final Thoughts 293 About the Author 297 Acknowledgements 299 Index 301

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Book SynopsisTable of ContentsForeword xxi Introduction xxiii Part I What You Must Know to Write Code Safe Enough to Put on the Internet 1 Chapter 1 Security Fundamentals 3 The Security Mandate: CIA 3 Confidentiality 4 Integrity 5 Availability 5 Assume Breach 7 Insider Threats 8 Defense in Depth 9 Least Privilege 11 Supply Chain Security 11 Security by Obscurity 13 Attack Surface Reduction 14 Hard Coding 15 Never Trust, Always Verify 15 Usable Security 17 Factors of Authentication 18 Exercises 20 Chapter 2 Security Requirements 21 Requirements 22 Encryption 23 Never Trust System Input 24 Encoding and Escaping 28 Third-Party Components 29 Security Headers: Seatbelts for Web Apps 31 Security Headers in Action 32 X-XSS-Protection 32 Content-Security-Policy (CSP) 32 X-Frame-Options 35 X-Content-Type-Options 36 Referrer-Policy 36 Strict-Transport-Security (HSTS) 37 Feature-Policy 38 X-Permitted-Cross-Domain-Policies 39 Expect-CT 39 Public Key Pinning Extension for HTTP (HPKP) 41 Securing Your Cookies 42 The Secure Flag 42 The HttpOnly Flag 42 Persistence 43 Domain 43 Path 44 Same-Site 44 Cookie Prefixes 45 Data Privacy 45 Data Classification 45 Passwords, Storage, and Other Important Decisions 46 HTTPS Everywhere 52 TLS Settings 53 Comments 54 Backup and Rollback 54 Framework Security Features 54 Technical Debt = Security Debt 55 File Uploads 56 Errors and Logging 57 Input Validation and Sanitization 58 Authorization and Authentication 59 Parameterized Queries 59 URL Parameters 60 Least Privilege 60 Requirements Checklist 61 Exercises 63 Chapter 3 Secure Design 65 Design Flaw vs. Security Bug 66 Discovering a Flaw Late 67 Pushing Left 68 Secure Design Concepts 68 Protecting Sensitive Data 68 Never Trust, Always Verify/Zero Trust/Assume Breach 70 Backup and Rollback 71 Server-Side Security Validation 73 Framework Security Features 74 Security Function Isolation 74 Application Partitioning 75 Secret Management 76 Re-authentication for Transactions (Avoiding CSRF) 76 Segregation of Production Data 77 Protection of Source Code 77 Threat Modeling 78 Exercises 82 Chapter 4 Secure Code 83 Selecting Your Framework and Programming Language 83 Example #1 85 Example #2 85 Example #3 86 Programming Languages and Frameworks: The Rule 87 Untrusted Data 87 HTTP Verbs 89 Identity 90 Session Management 91 Bounds Checking 93 Authentication (AuthN) 94 Authorization (AuthZ) 96 Error Handling, Logging, and Monitoring 99 Rules for Errors 100 Logging 100 Monitoring 101 Exercises 103 Chapter 5 Common Pitfalls 105 OWASP 105 Defenses and Vulnerabilities Not Previously Covered 109 Cross-Site Request Forgery 110 Server-Side Request Forgery 112 Deserialization 114 Race Conditions 115 Closing Comments 117 Exercises 117 Part II What You Should Do to Create Very Good Code 119 Chapter 6 Testing and Deployment 121 Testing Your Code 121 Code Review 122 Static Application Security Testing (SAST) 123 Software Composition Analysis (SCA) 125 Unit Tests 126 Infrastructure as Code (IaC) and Security as Code (SaC) 128 Testing Your Application 129 Manual Testing 130 Browsers 131 Developer Tools 131 Web Proxies 132 Fuzzing 133 Dynamic Application Security Testing (DAST) 133 VA/Security Assessment/PenTest 135 Testing Your Infrastructure 141 Testing Your Database 141 Testing Your APIs and Web Services 142 Testing Your Integrations 143 Testing Your Network 144 Deployment 145 Editing Code Live on a Server 146 Publishing from an IDE 146 “Homemade” Deployment Systems 147 Run Books 148 Contiguous Integration/Continuous Delivery/Continuous Deployment 148 Exercises 149 Chapter 7 An AppSec Program 151 Application Security Program Goals 152 Creating and Maintaining an Application Inventory 153 Capability to Find Vulnerabilities in Written, Running, and Third-Party Code 153 Knowledge and Resources to Fix the Vulnerabilities 154 Education and Reference Materials 155 Providing Developers with Security Tools 155 Having One or More Security Activities During Each Phase of Your SDLC 156 Implementing Useful and Effective Tooling 157 An Incident Response Team That Knows When to Call You 157 Continuously Improve Your Program Based on Metrics, Experimentation, and Feedback 159 Metrics 159 Experimentation 161 Feedback from Any and All Stakeholders 161 A Special Note on DevOps and Agile 162 Application Security Activities 162 Application Security Tools 164 Your Application Security Program 165 Exercises 166 Chapter 8 Securing Modern Applications and Systems 167 APIs and Microservices 168 Online Storage 171 Containers and Orchestration 172 Serverless 174 Infrastructure as Code (IaC) 175 Security as Code (SaC) 177 Platform as a Service (PaaS) 178 Infrastructure as a Service (IaaS) 179 Continuous Integration/Delivery/Deployment 180 Dev(Sec)Ops 180 DevSecOps 182 The Cloud 183 Cloud Computing 183 Cloud Native 184 Cloud Native Security 185 Cloud Workflows 185 Modern Tooling 186 IAST Interactive Application Security Testing 186 Runtime Application Security Protection 187 File Integrity Monitoring 187 Application Control Tools (Approved Software Lists) 187 Security Tools Created for DevOps Pipelines 188 Application Inventory Tools 188 Least Privilege and Other Policy Automation 189 Modern Tactics 189 Summary 191 Exercises 191 Part III Helpful Information on How to Continue to Create Very Good Code 193 Chapter 9 Good Habits 195 Password Management 196 Remove Password Complexity Rules 196 Use a Password Manager 197 Passphrases 198 Don’t Reuse Passwords 198 Do Not Implement Password Rotation 199 Multi-Factor Authentication 199 Incident Response 200 Fire Drills 201 Continuous Scanning 202 Technical Debt 202 Inventory 203 Other Good Habits 204 Policies 204 Downloads and Devices 204 Lock Your Machine 204 Privacy 205 Summary 206 Exercises 206 Chapter 10 Continuous Learning 207 What to Learn 208 Offensive = Defensive 208 Don’t Forget Soft Skills 208 Leadership != Management 209 Learning Options 209 Accountability 212 Create Your Plan 213 Take Action 214 Exercises 214 Learning Plan 216 Chapter 11 Closing Thoughts 217 Lingering Questions 218 When Have You Done Enough? 218 How Do You Get Management on Board? 220 How Do You Get Developers on Board? 221 Where Do You Start? 222 Where Do You Get Help? 223 Conclusion 223 Appendix A Resources 225 Introduction 225 Chapter 1: Security Fundamentals 225 Chapter 2: Security Requirements 226 Chapter 3: Secure Design 227 Chapter 4: Secure Code 228 Chapter 5: Common Pitfalls 228 Chapter 6: Testing and Deployment 229 Chapter 7: An AppSec Program 229 Chapter 8: Securing Modern Applications and Systems 230 Chapter 9: Good Habits 231 Chapter 10: Continuous Learning 231 Appendix B Answer Key 233 Chapter 1: Security Fundamentals 233 Chapter 2: Security Requirements 235 Chapter 3: Secure Design 236 Chapter 4: Secure Code 238 Chapter 5: Common Pitfalls 241 Chapter 6: Testing and Deployment 242 Chapter 7: An AppSec Program 244 Chapter 8: Securing Modern Applications and Systems 245 Chapter 9: Good Habits 247 Chapter 10: Continuous Learning 248 Index 249

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Book SynopsisTable of ContentsIntroduction xiv I Introduction to Algorithms 1 1 What Is an Algorithm? 3 Analyzing Algorithms 4 Constant Time 8 Logarithmic Time 9 Linear Time 10 Log-Linear Time 11 Quadratic Time 11 Cubic Time 13 Exponential Time 14 Best- Case vs. Worst-Case Complexity 15 Space Complexity 15 Why Is This Important? 16 Vocabulary 17 Challenge 18 2 Recursion 19 When to Use Recursion 23 Vocabulary 23 Challenge 23 3 Search Algorithms 25 Linear Search 25 When to Use a Linear Search 27 Binary Search 27 When to Use a Binary Search 30 Searching for Characters 32 Vocabulary 34 Challenge 35 4 Sorting Algorithms 37 Bubble Sort 37 When to Use Bubble Sort 41 Insertion Sort 42 When to Use Insertion Sort 45 Merge Sort 45 When to Use Merge Sort 52 Sorting Algorithms in Python 53 Vocabulary 54 Challenge 54 5 String Algorithms 55 Anagram Detection 55 Palindrome Detection 56 Last Digit 57 Caesar Cipher 58 Vocabulary 61 Challenge 61 6 Math 63 Binary 63 Bitwise Operators 66 FizzBuzz 70 Greatest Common Factor 72 Euclid’s Algorithm 74 Primes 75 Vocabulary 77 Challenge 78 7 Self- Taught Inspiration: Margaret Hamilton 79 II Data Structures. 81 8 What Is a Data Structure? 83 Vocabulary 85 Challenge 86 9 Arrays 87 Array Performance 88 Creating an Array 90 Moving Zeros 91 Combining Two Lists 94 Finding the Duplicates in a List 95 Finding the Intersection of Two Lists 98 Vocabulary 99 Challenge 100 10 Linked Lists 101 Linked List Performance 103 Create a Linked List 104 Search a Linked List 107 Removing a Node from a Linked List 108 Reverse a Linked List 109 Finding a Linked List Cycle 110 Vocabulary 111 Challenges 112 11 Stacks 113 When to Use Stacks 114 Creating a Stack 115 Using Stacks to Reverse Strings 119 Min Stack 120 Stacked Parentheses 123 Vocabulary 125 Challenges 125 12 Queues 127 When to Use Queues 128 Creating a Queue 129 Python’s Built- In Queue Class 134 Create a Queue Using Two Stacks 134 Vocabulary 136 Challenge 136 13 Hash Tables 137 When to Use Hash Tables 140 Characters in a String 141 Two Sum 143 Vocabulary 144 Challenge 145 14 Binary Trees 147 When to Use Trees 150 Creating a Binary Tree 153 Breadth- First Tree Traversal 155 More Tree Traversals 157 Invert a Binary Tree 160 Vocabulary 162 Challenges 162 15 Binary Heaps 163 When to Use Heaps 167 Creating a Heap 167 Connecting Ropes with Minimal Cost 169 Vocabulary 171 Challenge 171 16 Graphs 173 When to Use Graphs 177 Creating a Graph 178 Dijkstra’s Algorithm 180 Vocabulary 186 Challenge 187 17 Self- Taught Inspiration: Elon Musk 189 18 Next Steps 191 What’s Next? 191 Climbing the Freelance Ladder 192 How to Get an Interview 192 How to Prepare for a Technical Interview 193 Additional Resources 194 Final Thoughts 194 Index 195

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Book SynopsisTable of ContentsForeword xix Introduction xxi Domain 1: Security and Risk Management 1 Understand, Adhere to, and Promote Professional Ethics 2 (ISC)2 Code of Professional Ethics 2 Organizational Code of Ethics 3 Understand and Apply Security Concepts 4 Confidentiality 4 Integrity 5 Availability 6 Limitations of the CIA Triad 7 Evaluate and Apply Security Governance Principles 8 Alignment of the Security Function to Business Strategy, Goals, Mission, and Objectives 9 Organizational Processes 10 Organizational Roles and Responsibilities 14 Security Control Frameworks 15 Due Care and Due Diligence 22 Determine Compliance and Other Requirements 23 Legislative and Regulatory Requirements 23 Industry Standards and Other Compliance Requirements 25 Privacy Requirements 27 Understand Legal and Regulatory Issues That Pertain to Information Security in a Holistic Context 28 Cybercrimes and Data Breaches 28 Licensing and Intellectual Property Requirements 36 Import/Export Controls 39 Transborder Data Flow 40 Privacy 41 Understand Requirements for Investigation Types 48 Administrative 49 Criminal 50 Civil 52 Regulatory 53 Industry Standards 54 Develop, Document, and Implement Security Policy, Standards, Procedures, and Guidelines 55 Policies 55 Standards 56 Procedures 57 Guidelines 57 Identify, Analyze, and Prioritize Business Continuity Requirements 58 Business Impact Analysis 59 Develop and Document the Scope and the Plan 61 Contribute to and Enforce Personnel Security Policies and Procedures 63 Candidate Screening and Hiring 63 Employment Agreements and Policies 64 Onboarding, Transfers, and Termination Processes 65 Vendor, Consultant, and Contractor Agreements and Controls 67 Compliance Policy Requirements 67 Privacy Policy Requirements 68 Understand and Apply Risk Management Concepts 68 Identify Threats and Vulnerabilities 68 Risk Assessment 70 Risk Response/Treatment 72 Countermeasure Selection and Implementation 73 Applicable Types of Controls 75 Control Assessments 76 Monitoring and Measurement 77 Reporting 77 Continuous Improvement 78 Risk Frameworks 78 Understand and Apply Threat Modeling Concepts and Methodologies 83 Threat Modeling Concepts 84 Threat Modeling Methodologies 85 Apply Supply Chain Risk Management Concepts 88 Risks Associated with Hardware, Software, and Services 88 Third-Party Assessment and Monitoring 89 Minimum Security Requirements 90 Service-Level Requirements 90 Frameworks 91 Establish and Maintain a Security Awareness, Education, and Training Program 92 Methods and Techniques to Present Awareness and Training 93 Periodic Content Reviews 94 Program Effectiveness Evaluation 94 Summary 95 Domain 2: Asset Security 97 Identify and Classify Information and Assets 97 Data Classification and Data Categorization 99 Asset Classification 101 Establish Information and Asset Handling Requirements 104 Marking and Labeling 104 Handling 105 Storage 105 Declassification 106 Provision Resources Securely 108 Information and Asset Ownership 108 Asset Inventory 109 Asset Management 112 Manage Data Lifecycle 115 Data Roles 116 Data Collection 120 Data Location 120 Data Maintenance 121 Data Retention 122 Data Destruction 123 Data Remanence 123 Ensure Appropriate Asset Retention 127 Determining Appropriate Records Retention 129 Records Retention Best Practices 130 Determine Data Security Controls and Compliance Requirements 131 Data States 133 Scoping and Tailoring 135 Standards Selection 137 Data Protection Methods 141 Summary 144 Domain 3: Security Architecture and Engineering 147 Research, Implement, and Manage Engineering Processes Using Secure Design Principles 149 ISO/IEC 19249 150 Threat Modeling 157 Secure Defaults 160 Fail Securely 161 Separation of Duties 161 Keep It Simple 162 Trust, but Verify 162 Zero Trust 163 Privacy by Design 165 Shared Responsibility 166 Defense in Depth 167 Understand the Fundamental Concepts of Security Models 168 Primer on Common Model Components 168 Information Flow Model 169 Noninterference Model 169 Bell–LaPadula Model 170 Biba Integrity Model 172 Clark–Wilson Model 173 Brewer–Nash Model 173 Take-Grant Model 175 Select Controls Based Upon Systems Security Requirements 175 Understand Security Capabilities of Information Systems 179 Memory Protection 180 Secure Cryptoprocessor 182 Assess and Mitigate the Vulnerabilities of Security Architectures, Designs, and Solution Elements 187 Client-Based Systems 187 Server-Based Systems 189 Database Systems 191 Cryptographic Systems 194 Industrial Control Systems 200 Cloud-Based Systems 203 Distributed Systems 207 Internet of Things 208 Microservices 212 Containerization 214 Serverless 215 Embedded Systems 216 High-Performance Computing Systems 219 Edge Computing Systems 220 Virtualized Systems 221 Select and Determine Cryptographic Solutions 224 Cryptography Basics 225 Cryptographic Lifecycle 226 Cryptographic Methods 229 Public Key Infrastructure 243 Key Management Practices 246 Digital Signatures and Digital Certificates 250 Nonrepudiation 252 Integrity 253 Understand Methods of Cryptanalytic Attacks 257 Brute Force 258 Ciphertext Only 260 Known Plaintext 260 Chosen Plaintext Attack 260 Frequency Analysis 261 Chosen Ciphertext 261 Implementation Attacks 261 Side-Channel Attacks 261 Fault Injection 263 Timing Attacks 263 Man-in-the-Middle 263 Pass the Hash 263 Kerberos Exploitation 264 Ransomware 264 Apply Security Principles to Site and Facility Design 265 Design Site and Facility Security Controls 265 Wiring Closets/Intermediate Distribution Facilities 266 Server Rooms/Data Centers 267 Media Storage Facilities 268 Evidence Storage 269 Restricted and Work Area Security 270 Utilities and Heating, Ventilation, and Air Conditioning 272 Environmental Issues 275 Fire Prevention, Detection, and Suppression 277 Summary 281 Domain 4: Communication and Network Security 283 Assess and Implement Secure Design Principles in Network Architectures 283 Open System Interconnection and Transmission Control Protocol/Internet Protocol Models 285 The OSI Reference Model 286 The TCP/IP Reference Model 299 Internet Protocol Networking 302 Secure Protocols 311 Implications of Multilayer Protocols 313 Converged Protocols 315 Microsegmentation 316 Wireless Networks 319 Cellular Networks 333 Content Distribution Networks 334 Secure Network Components 335 Operation of Hardware 335 Repeaters, Concentrators, and Amplifiers 341 Hubs 341 Bridges 342 Switches 342 Routers 343 Gateways 343 Proxies 343 Transmission Media 345 Network Access Control 352 Endpoint Security 354 Mobile Devices 355 Implement Secure Communication Channels According to Design 357 Voice 357 Multimedia Collaboration 359 Remote Access 365 Data Communications 371 Virtualized Networks 373 Third-Party Connectivity 374 Summary 374 Domain 5: Identity and Access Management 377 Control Physical and Logical Access to Assets 378 Access Control Definitions 378 Information 379 Systems 380 Devices 381 Facilities 383 Applications 386 Manage Identification and Authentication of People, Devices, and Services 387 Identity Management Implementation 388 Single/Multifactor Authentication 389 Accountability 396 Session Management 396 Registration, Proofing, and Establishment of Identity 397 Federated Identity Management 399 Credential Management Systems 399 Single Sign-On 400 Just-In-Time 401 Federated Identity with a Third-Party Service 401 On Premises 402 Cloud 403 Hybrid 403 Implement and Manage Authorization Mechanisms 404 Role-Based Access Control 405 Rule-Based Access Control 405 Mandatory Access Control 406 Discretionary Access Control 406 Attribute-Based Access Control 407 Risk-Based Access Control 408 Manage the Identity and Access Provisioning Lifecycle 408 Account Access Review 409 Account Usage Review 411 Provisioning and Deprovisioning 411 Role Definition 412 Privilege Escalation 413 Implement Authentication Systems 414 OpenID Connect/Open Authorization 414 Security Assertion Markup Language 415 Kerberos 416 Remote Authentication Dial-In User Service/Terminal Access Controller Access Control System Plus 417 Summary 418 Domain 6: Security Assessment and Testing 419 Design and Validate Assessment, Test, and Audit Strategies 420 Internal 421 External 422 Third-Party 423 Conduct Security Control Testing 423 Vulnerability Assessment 423 Penetration Testing 428 Log Reviews 435 Synthetic Transactions 435 Code Review and Testing 436 Misuse Case Testing 437 Test Coverage Analysis 438 Interface Testing 439 Breach Attack Simulations 440 Compliance Checks 441 Collect Security Process Data 442 Technical Controls and Processes 443 Administrative Controls 443 Account Management 444 Management Review and Approval 445 Management Reviews for Compliance 446 Key Performance and Risk Indicators 447 Backup Verification Data 450 Training and Awareness 450 Disaster Recovery and Business Continuity 451 Analyze Test Output and Generate Report 452 Typical Audit Report Contents 453 Remediation 454 Exception Handling 455 Ethical Disclosure 456 Conduct or Facilitate Security Audits 458 Designing an Audit Program 458 Internal Audits 459 External Audits 460 Third-Party Audits 460 Summary 461 Domain 7: Security Operations 463 Understand and Comply with Investigations 464 Evidence Collection and Handling 465 Reporting and Documentation 467 Investigative Techniques 469 Digital Forensics Tools, Tactics, and Procedures 470 Artifacts 475 Conduct Logging and Monitoring Activities 478 Intrusion Detection and Prevention 478 Security Information and Event Management 480 Continuous Monitoring 481 Egress Monitoring 483 Log Management 484 Threat Intelligence 486 User and Entity Behavior Analytics 488 Perform Configuration Management 489 Provisioning 490 Asset Inventory 492 Baselining 492 Automation 493 Apply Foundational Security Operations Concepts 494 Need-to-Know/Least Privilege 494 Separation of Duties and Responsibilities 495 Privileged Account Management 496 Job Rotation 498 Service-Level Agreements 498 Apply Resource Protection 499 Media Management 500 Media Protection Techniques 501 Conduct Incident Management 502 Incident Management Plan 503 Detection 505 Response 506 Mitigation 507 Reporting 508 Recovery 510 Remediation 510 Lessons Learned 511 Operate and Maintain Detective and Preventative Measures 511 Firewalls 512 Intrusion Detection Systems and Intrusion Prevention Systems 514 Whitelisting/Blacklisting 515 Third-Party-Provided Security Services 515 Sandboxing 517 Honeypots/Honeynets 517 Anti-malware 518 Machine Learning and Artificial Intelligence Based Tools 518 Implement and Support Patch and Vulnerability Management 519 Patch Management 519 Vulnerability Management 521 Understand and Participate in Change Management Processes 522 Implement Recovery Strategies 523 Backup Storage Strategies 524 Recovery Site Strategies 527 Multiple Processing Sites 527 System Resilience, High Availability, Quality of Service, and Fault Tolerance 528 Implement Disaster Recovery Processes 529 Response 529 Personnel 530 Communications 531 Assessment 532 Restoration 533 Training and Awareness 534 Lessons Learned 534 Test Disaster Recovery Plans 535 Read-through/Tabletop 536 Walkthrough 536 Simulation 537 Parallel 537 Full Interruption 537 Participate in Business Continuity Planning and Exercises 538 Implement and Manage Physical Security 539 Perimeter Security Controls 541 Internal Security Controls 543 Address Personnel Safety and Security Concerns 545 Travel 545 Security Training and Awareness 546 Emergency Management 546 Duress 547 Summary 548 Domain 8: Software Development Security 549 Understand and Integrate Security in the Software Development Life Cycle (SDLC) 550 Development Methodologies 551 Maturity Models 561 Operation and Maintenance 567 Change Management 568 Integrated Product Team 571 Identify and Apply Security Controls in Software Development Ecosystems 572 Programming Languages 572 Libraries 577 Toolsets 578 Integrated Development Environment 579 Runtime 580 Continuous Integration and Continuous Delivery 581 Security Orchestration, Automation, and Response 583 Software Configuration Management 585 Code Repositories 586 Application Security Testing 588 Assess the Effectiveness of Software Security 590 Auditing and Logging of Changes 590 Risk Analysis and Mitigation 595 Assess Security Impact of Acquired Software 599 Commercial Off-the-Shelf 599 Open Source 601 Third-Party 602 Managed Services (SaaS, IaaS, PaaS) 602 Define and Apply Secure Coding Guidelines and Standards 604 Security Weaknesses and Vulnerabilities at the Source-Code Level 605 Security of Application Programming Interfaces 613 API Security Best Practices 613 Secure Coding Practices 618 Software-Defined Security 621 Summary 624 Index 625

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Book SynopsisThis book presents an accessible introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, it offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners.  Trade ReviewTrumpets please! This lucidly written report on data-driven storytelling lays out the compelling benefits and substantial challenges of this potent journalistic innovation. The strong team of authors offer fresh thinking and thoughtful guidance on exploration, explanation, engagement, ethics, and evaluation. Packed with examples for practitioners and references for researchers, this book opens up fresh possibilities that extend information visualization into decision-making, policy-shifting, and mind-changing applications.--Ben Shneiderman, University of MarylandData-Driven Storytelling presents an accessible and informative introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, Data-Driven Storytelling offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners. The newest addition to the simply outstanding CRC Press 'A K Peters Visualization Series', Data-Driven Storytelling is unreservedly recommended for professional, corporate, college, and university library Computer Science & Engineering collections and supplemental studies reading lists.--Midwest Book Review, May 2018 Data-Driven Storytelling promotes an efficient way of data-driven storytelling in professionalism and its profound implications. This approach involves visualizations, explorations, explanations, curated visuals, narrative design patterns, process from analysis to communication, impressing the audience, ethical guidelines and evaluation methods on successful the data driven storytelling.--Ramalingam Shanmugam, Journal of Statistical Computation and Simulation“This bible of data-driven storytelling covers everything you need to know about the topic, from storytelling techniques (including scrollytelling) and narrative design patterns to evaluation and ethics in storytelling, providing readers with explanations and examples of the concepts described as well as extensive reference material. All of this is expressed in an accurate, concise, and clear way.”--Lorenzo Amabili, University of Groningen, Book Review in NightingaleTrumpets please! This lucidly written report on data-driven storytelling lays out the compelling benefits and substantial challenges of this potent journalistic innovation. The strong team of authors offer fresh thinking and thoughtful guidance on exploration, explanation, engagement, ethics, and evaluation. Packed with examples for practitioners and references for researchers, this book opens up fresh possibilities that extend information visualization into decision-making, policy-shifting, and mind-changing applications.--Ben Shneiderman, University of MarylandData-Driven Storytelling presents an accessible and informative introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, Data-Driven Storytelling offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners. The newest addition to the simply outstanding CRC Press 'A K Peters Visualization Series', Data-Driven Storytelling is unreservedly recommended for professional, corporate, college, and university library Computer Science & Engineering collections and supplemental studies reading lists.--Midwest Book Review, May 2018 Data-Driven Storytelling promotes an efficient way of data-driven storytelling in professionalism and its profound implications. This approach involves visualizations, explorations, explanations, curated visuals, narrative design patterns, process from analysis to communication, impressing the audience, ethical guidelines and evaluation methods on successful the data driven storytelling.--Ramalingam Shanmugam, Journal of Statistical Computation and Simulation“This bible of data-driven storytelling covers everything you need to know about the topic, from storytelling techniques (including scrollytelling) and narrative design patterns to evaluation and ethics in storytelling, providing readers with explanations and examples of the concepts described as well as extensive reference material. All of this is expressed in an accurate, concise, and clear way.”--Lorenzo Amabili, University of Groningen, Book Review in NightingaleTable of ContentsIntroduction. From Cognitive to Design Principles. Exploration and Explanation in Data-Driven Storytelling. Data-Driven Storytelling Techniques: Analysis of a Curated Collection of Visual Stories. Narrative Design Patterns for Data-Driven Storytelling. Watches to Augmented Reality Devices and Gadgets for Data-Driven Storytelling. From Analysis to Communication Supporting the Lifecycle of a Story. Organizing the Work of Data-Driven Visual Storytelling. Communicating Data to an Audience.Ethics in Data-Driven Visual Storytelling. Evaluating Data-Driven Stories & Storytelling Tools.

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Book Synopsis Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Quickly write innovative programs for your micro:bitâno experience necessary! This easy-to-follow guide shows, step-by-step, how to quickly get started with programming and creating fun applications on your micro:bit.. Written in the straightforward style that Dr. Simon Monk is famous for, Programming the BBC micro:bit: Getting Started with MicroPython begins with basic concepts and gradually progresses to more advanced techniques. You will discover how to use the micro:bit's built-in hardware, use the LED display, accept input from sensors, attach external electronics, and handle wireless communication. â

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Book SynopsisTough Test Questions? Missed Lectures? Not Enough Time?Fortunately, thereâs Schaumâs. More than 40 million students have trusted Schaumâs to help them succeed in the classroom and on exams. Schaumâs is the key to faster learning and higher grades in every subject. Each Outline presents all the essential course information in an easy-to-follow, topic-by-topic format. You also get hundreds of examples, sovled problems, and practice exercises to test your skills. This Schaumâs Outline gives you:â  750 exercises with answersâ  Introduction to the most widely used language in technical and scientific computingâ  Reference index of the most useful commands in Mathematicaâ Support for all major textbooks for courses in MathematicaSchaumâs reinforces the main concepts required in your course and offers

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Book Synopsis Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Donât Let the Real Test Be Your First Test! This fully updated self-study guide offers complete coverage of all eight Certified Information Systems Security Professional exam domains developed by the International Information Systems Security Certification Consortium (ISC)2 . To reinforce important skills and facilitate retention, every question is accompanied by in-depth explanations for both correct and incorrect answers. Designed to help you pass the test with ease, this book is the ideal companion to the bestselling CISSP All-in-One Exam GuideTable of ContentsChapter 1: Security and Risk ManagementChapter 2: Asset SecurityChapter 3: Security EngineeringChapter 4: Communication and Network SecurityChapter 5: Identity and Access ManagementChapter 6: Security Assessment and TestingChapter 7: Security OperationsChapter 8: Software Development Security

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Book SynopsisPublisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.A comprehensive introduction to the mathematical principles and algorithms in statistical signal processing and modern neural networks. This text is an expanded version of a graduate course on advanced signal processing at the Johns Hopkins University Whiting school program for professionals with students from electrical engineering, physics, computer and data science, and mathematics backgrounds.  It covers the theory underlying applications in statistical signal processing including spectral estimation, linear prediction, adaptive filters, and optimal processing of uniform spatial arrays.  Unique among books on the subject, it also includes a comprehensive introduction to modern neural networks with examples in time series prediction and image

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Book SynopsisDevelop a strong understanding of IT project management as you learn to apply today's most effective project management tools and techniques with the unique approach found in Schwalbe's INFORMATION TECHNOLOGY PROJECT MANAGEMENT, 9E. Examine the latest developments and skills as you prepare for the Project Management Professional (PMP) or Certified Associate in Project Management (CAPM) exams. This edition reflects content from the latest PMBOK Guide, 6E and the Agile Practice Guide while providing a meaningful context. Examples from familiar companies featured in today's news discussion, exercises and cases reinforce learning. Time-saving template files assist in completing tasks. Agile information, a guide to using Microsoft Project 2016 and MindTap online resources will help you master today's most marketable IT project management skills.Table of Contents1. Introduction to Project Management. 2. The Project Management and Information Technology Context. 3. The Project Management Process Groups: A Case Study. 4. Project Integration Management. 5. Project Scope Management. 6. Project Schedule Management. 7. Project Cost Management. 8. Project Quality Management. 9. Project Resource Management. 10. Project Communications Management. 11. Project Risk Management. 12. Project Procurement Management. 13. Project Stakeholder Managements. Appendix A: Guide to Using Microsoft�� Project 2016.

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Book SynopsisTable of ContentsIntroduction: Why You Need This Book as a Retail Leader 1 Section 1 Introduction to the AI Revolution 11 1 How Ai Has Revolutionized Many Other Industries over the Last 20 Years 13 2 The Three Myths of How AI Will Transform Retail 37 3 How AI Will Automate and Optimize Retail 51 4 Level- Setting the AI Doomsday- ism 67 Section 2 AI Theory 75 5 What Is AI? 77 6 From CPUs to GPUs 84 7 Optimization 88 8 Measuring AI Performance 94 9 AI Learning Techniques 100 10 Simulators and AI 111 11 OODA Loops 116 12 Hierarchy of Data Maturity 120 13 A “General Theory for Retail AI” 125 Section 3 Applications of AI in Retail 137 14 The Inefficiencies in Retail Today 139 15 AI for Merchandising 143 16 AI for Inventory, Ordering, and Supply Chain Management 153 17 AI for Replenishment and Labor Management 177 18 AI for Labor Budgets and Scheduling 193 19 AI for E- Commerce and Customer Service 199 20 AI for Warehouse and Distribution Centers 212 21 AI for Checkout 227 22 AI for Pricing and Promotion 254 23 Other AI Use Cases 263 Section 4 Implementation 269 24 Create your “AI Strategy and Road Map” 271 25 Buying vs. Building AI 285 26 How to Run a Proof of Concept Bake- off Effectively 292 27 Transitioning to a Fact- based, Data- driven Culture 303 About the Author 309 Index 311

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Book SynopsisTransform your company's AI and data frameworks to unlock the true power of disruptive new tech In From Data to Profit: How Businesses Leverage Data to Grow Their Top and Bottom Lines, accomplished entrepreneur and AI strategist Vineet Vashishta delivers an engaging and insightful new take on making the most of data, artificial intelligence, and technology at your company. You'll learn to change the culture, strategy, structure, and operational framework of your company to take full advantage of disruptive advances in tech. The author explores fascinating work being undertaken by firms in the real world, as well as high-value use cases and innovative projects and products made possible by realigning organizational frameworks using the capabilities of new technologies. He explains how to get everyone in your company on the same page, following a single framework, in a way that ensures individual departments get what they want and need. You'll learn to outline aTable of ContentsIntroduction vii Chapter 1 Overview of the Frameworks 1 Chapter 2 There Is No Finish Line 15 Chapter 3 Why Is Transformation So Hard? 37 Chapter 4 Final vs. Evolutionary Decision Culture 59 Chapter 5 The Disruptor’s Mindset 71 Chapter 6 A Data- Driven Definition of Strategy 89 Chapter 7 The Monolith—Technical Strategy 103 Chapter 8 Who Survives Disruption? 125 Chapter 9 Data—The Business’s Hidden Giant 139 Chapter 10 The AI Maturity Model 155 Chapter 11 The Human-Machine Maturity Model 171 Chapter 12 A Vision for AI Opportunities 185 Chapter 13 Discovering AI Treasure 201 Chapter 14 Large Model Monetization Strategies—Quick Wins 215 Chapter 15 Large Model Monetization Strategies—The Bigger Picture 229 Chapter 16 Assessing the Business’s AI Maturity 251 Chapter 17 Building the Data and AI Strategy 273 Chapter 18 Building the Center of Excellence 287 Chapter 19 Data and AI Product Strategy 301 Index 325

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Book SynopsisDramatically lower the cyber risk posed by third-party software and vendors in your organization In Zero Trust and Third-Party Risk, veteran cybersecurity leader Gregory Rasner delivers an accessible and authoritative walkthrough of the fundamentals and finer points of the zero trust philosophy and its application to the mitigation of third-party cyber risk. In this book, you'll explore how to build a zero trust program and nurture it to maturity. You will also learn how and why zero trust is so effective in reducing third-party cybersecurity risk. The author uses the story of a fictional organizationKC Enterprisesto illustrate the real-world application of zero trust principles. He takes you through a full zero trust implementation cycle, from initial breach to cybersecurity program maintenance and upkeep. You'll also find: Explanations of the processes, controls, and programs that make up the zero trust doctrineDescriptions of the five pillars of implementing zero trust with third-party vendorsNumerous examples, use-cases, and stories that highlight the real-world utility of zero trustAn essential resource for board members, executives, managers, and other business leaders, Zero Trust and Third-Party Risk will also earn a place on the bookshelves of technical and cybersecurity practitioners, as well as compliance professionals seeking effective strategies to dramatically lower cyber risk.Table of ContentsForeword xiii INTRODUCTION: Reduce the Blast Radius xvii Part I Zero Trust and Third-Party Risk Explained 1 Chapter 1 Overview of Zero Trust and Third-Party Risk 3 Zero Trust 3 What Is Zero Trust? 4 The Importance of Strategy 5 Concepts of Zero Trust 6 1. Secure Resources 7 2. Least Privilege and Access Control 8 3. Ongoing Monitoring and Validation 11 Zero Trust Concepts and Definitions 13 Multifactor Authentication 13 Microsegmentation 14 Protect Surface 15 Data, Applications, Assets, Services (DAAS) 15 The Five Steps to Deploying Zero Trust 16 Step 1: Define the Protect Surface 16 Step 2: Map the Transaction Flows 17 Step 3: Build the Zero Trust Architecture 17 Step 4: Create the Zero Trust Policy 17 Step 5: Monitor and Maintain the Network 19 Zero Trust Frameworks and Guidance 20 Zero Trust Enables Business 22 Cybersecurity and Third-Party Risk 22 What Is Cybersecurity and Third-Party Risk? 23 Overview of How to Start or Mature a Program 25 Start Here 25 Intake, Questions, and Risk-Based Approach 27 Remote Questionnaires 28 Contract Controls 29 Physical Validation 30 Continuous Monitoring 31 Disengagement and Cybersecurity 33 Reporting and Analytics 34 ZT with CTPR 35 Why Zero Trust and Third-Party Risk? 35 How to Approach Zero Trust and Third-Party Risk 37 ZT/CTPR OSI Model 38 Chapter 2 Zero Trust and Third-Party Risk Model 43 Zero Trust and Third-Party Users 43 Access Control Process 44 Identity: Validate Third-Party Users with Strong Authentication 45 Five Types of Strong Authentication 47 Identity and Access Management 50 Privileged Access Management 52 Device/Workload: Verify Third-Party User Device Integrity 54 Access: Enforce Least-Privilege Access for Third-Party Users to Data and Apps 57 Groups 57 Work Hours 58 Geo-Location 58 Device-Based Restrictions 58 Auditing 59 Transaction: Scan All Content for Third-Party Malicious Activity 59 IDS/IPS 60 DLP 60 SIEM 61 UBAD 61 Governance 62 Zero Trust and Third-Party Users Summary 62 Zero Trust and Third-Party Applications 63 Identity: Validate Third-Party Developers, DevOps, and Admins with Strong Auth 64 Privileged User Groups 64 Multifactor Authentication 64 Just-in-Time Access 65 Privileged Access Management 65 Audit and Logging 66 Device/Workload: Verify Third-Party Workload Integrity 66 Access: Enforce Least-Privilege Access for Third-Party Workloads Accessing Other Workloads 67 Transaction: Scan All Content for Third-Party Malicious Activity and Data Theft 68 Zero Trust and Third-Party Applications Summary 70 Zero Trust and Third-Party Infrastructure 70 Identity: Validate Third-Party Users with Access to Infrastructure 71 Device/Workload: Identify All Third-Party Devices (Including IoT) 72 Software-Defined Perimeter 74 Encryption 74 Updates 75 Enforce Strong Passwords 75 Vulnerability and Secure Development Management 75 Logging and Monitoring 76 Access: Enforce Least-Privilege Access Segmentation for Third-Party Infrastructure 76 Transaction: Scan All Content Within the Infra for Third-Party Malicious Activity and Data Theft 77 Zero Trust and Third-Party Infrastructure Summary 78 Chapter 3 Zero Trust and Fourth-Party Cloud (SaaS) 79 Cloud Service Providers and Zero Trust 80 Zero Trust in Amazon Web Services 81 Zero Trust in Azure 83 Zero Trust in Azure Storage 85 Zero Trust on Azure Virtual Machines 87 Zero Trust on an Azure Spoke VNet 87 Zero Trust on an Azure Hub VNet 88 Zero Trust in Azure Summary 88 Zero Trust in Google Cloud 88 Identity-Aware Proxy 89 Access Context Manager 90 Zero Trust in Google Cloud Summary 91 Vendors and Zero Trust Strategy 91 Zero Trust at Third Parties as a Requirement 91 A Starter Zero Trust Security Assessment 92 A Zero Trust Maturity Assessment 95 Pillar 1: Identity 98 Pillar 2: Device 101 Pillar 3: Network/Environment 104 Pillar 4: Application/Workload 107 Pillar 5: Data 110 Cross-cutting Capabilities 113 Zero Trust Maturity Assessment for Critical Vendors 115 Part I: Zero Trust and Third-Party Risk Explained Summary 119 Part II Apply the Lessons from Part I 121 Chapter 4 KC Enterprises: Lessons Learned in ZT and CTPR 123 Kristina Conglomerate Enterprises 124 KC Enterprises’ Cyber Third-Party Risk Program 127 KC Enterprises’ Cybersecurity Policy 127 Scope 127 Policy Statement and Objectives 128 Cybersecurity Program 128 Classification of Information Assets 129 A Really Bad Day 130 Then the Other Shoe Dropped 133 Chapter 5 Plan for a Plan 139 KC's ZT and CTPR Journey 139 Define the Protect Surface 143 Map Transaction Flows 146 Architecture Environment 148 Deploy Zero Trust Policies 159 Logical Policies and Environmental Changes 159 Zero Trust for Third-Party Users at KC Enterprises 161 Third-Party User and Device Integrity 161 Third-Party Least-Privileged Access 163 Third-Party User and Device Scanning 165 Zero Trust for Third-Party Applications at KC Enterprises 166 Third-Party Application Development and Workload Integrity 166 Third-Party Application Least-Privileged Access Workload to Workload 168 Third-Party Application Scanning 168 Zero Trust for Third-Party Infrastructure at KC Enterprises 169 Third-Party User Access to Infrastructure 169 Third-Party Device Integrity 170 Third-Party Infrastructure Segmentation 170 Third-Party Infrastructure Scanning 171 Written Policy Changes 172 Identity and Access Management Program 172 Vulnerability Management Program 173 Cybersecurity Incident Management Program 174 Cybersecurity Program 175 Cybersecurity Third-Party Risk Program 175 Third-Party Security Standard 177 Information Security Addendum 181 Assessment Alignment and Due Diligence 198 Third-Party Risk Management Program 202 Legal Policies 203 Monitor and Maintain 205 Part II: Apply the Lessons from Summary 206 Acknowledgments 209 About the Author 211 About the Technical Editor 211 Index 213

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Book SynopsisA much-needed guide to implementing new technology in workspaces From experts in the field comes Machine Learning Upgrade: A Data Scientist''s Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best practices at the intersection of management, large language models (LLMs), machine learning, and data science. This groundbreaking book will change the way that you view the pipeline of data science. The authors provide an introduction to modern machine learning, showing you how it can be viewed as a holistic, end-to-end systemnot just shiny new gadget in an otherwise unchanged operational structure. By adopting a data-centric view of the world, you can begin to see unstructured data and LLMs as the foundation upon which you can build countless applications and business solutions. This book explores a whole world of decision making that hasn''t been codified yet, enabling you to forge the future using emerging best practi

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Book SynopsisAccelerate your programming with the most popular AI coding tool on the market: GitHub Copilot In Programming with GitHub Copilot: Write Better Code Faster, veteran software developer and GitHub community hero Kurt Dowswell delivers an insightful and hands-on exploration of GitHub''s powerful, new AI coding assistant, Copilot. In the book, you''ll discover how to use the tool''s capabilities to push the boundaries of what you thought was possible in programming. Even if you''ve used autocomplete toolslike VS Code''s TabNine extensionbefore, you''ll be floored by GitHub Copilot''s potential to transform the way you code. You''ll learn how to install, configure, and use the software, from employing it''s most common and widely used features to deploying business and enterprise functionality. You''ll even discover how to fix runtime and compilation bugs and write unit, integration, and end-to-end tests. You''ll also find: Prompt strategies to get GitHub

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Book SynopsisProviding guidance that helps students practice and troubleshoot their exam technique,these books send them into their exam with the confidence to aim for the best grades.- Enables students to avoid common misconceptions and mistakes by highlighting them throughout- Builds students'' skills constructing and writing answers as they progress through a range of practice questions- Allows students to mark their own responses and easily identify areas for improvement using the answers in the back of the book- Helps students target their revision and focus on important concepts and skills with key objectives at the beginning of every chapter- Ensures that students maximise their time in the exam by including examiner''s tops and suggestions on how to approach the questionsThis title has not been through the Cambridge International endorsement process.

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Book SynopsisTable of ContentsPart I: Database Systems Chapter 1: The Database Approach Chapter 2: Data Models Chapter 3: Relational Model Characteristics Chapter 4: Relational Algebra and Calculus Part II: Database Alternatives Chapter 5: Data Modelling with Entity Relationship Diagrams Chapter 6: Data Modelling Advanced Concepts Chapter 7: Normalising Database Designs Part III: Database Programming Chapter 8: Beginning Structured Query Language Chapter 9: Procedural Language SQL and Advanced SQL Part IV: Database Design Chapter 10: Database Development Process Chapter 11: Conceptual, Logical and Physical Database Design Part V: Implementation Alternatives Chapter 12: Managing Transactions and Concurrency Chapter 13: Managing Database and SQL Performance Part VI: Database Management Chapter 14: Distributed Databases Chapter 15: Databases for Business Intelligence Chapter 16: Big Data and NoSQL Chapter 17: Database Connectivity and Web Technologies

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Book SynopsisRead this if you want to understand how to shape our technological future and reinvigorate democracy along the way. -- Reed Hastings, co-founder and CEO of Netflix__________A forward-thinking manifesto from three Stanford professors which reveals how big tech's obsession with optimization and efficiency has sacrificed fundamental human values and outlines steps we can take to change course, renew our democracy, and save ourselves.__________In no more than the blink of an eye, a naïve optimism about technology's liberating potential has given way to a dystopian obsession with biased algorithms, surveillance capitalism, and job-displacing robots. Yet too few of us see any alternative to accepting the onward march of technology. We have simply accepted a technological future designed for us by technologists, the venture capitalists who fund them, and the politicians who give them free rein.It doesn't need to be this way.System Error exposes the root of our current predicament: how big tech's relentless focus on optimization is driving a future that reinforces discrimination, erodes privacy, displaces workers, and pollutes the information we get.Armed with an understanding of how technologists think and exercise their power, three Stanford professors - a philosopher working at the intersection of tech and ethics, a political scientist who served under Obama, and the director of the undergraduate Computer Science program at Stanford (also an early Google engineer) - reveal how we can hold that power to account.As the dominance of big tech becomes an explosive societal conundrum, they share their provocative insights and concrete solutions to help everyone understand what is happening, what is at stake, and what we can do to control technology instead of letting it control us.

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Book SynopsisThe second edition of C# and Game Programming offers the same practical, hands-on approach as the first edition to learning the C# language through classic arcade game applications. Complete source code for games like Battle Bit, Asteroid Miner, and Battle Tennis, included on the CD-ROM, demonstrates programming strategies and complements the comprehensive treatment of C# in the text. From the basics of adding graphics and sound to games, to advanced concepts such as the .Net framework and object-oriented programming, this book provides the foundations for a beginner to become a full-fledged programmer. New in this edition: - Supports DirectX 9.0 - Revised programs and examples - Improved frame rate for game examplesTrade Review"C# and Game Programming is a useful all-around resource for anyone looking to get off the ground and start learning what C# can really do." -Wisconsin Bookwatch, June 2005Table of ContentsPART ONE: Programming Basics, Chapter One: C# from the Beginning, Chapter Two: Branches, Loops, and Functions PART TWO: Game Programming Basics, Chapter Three: Introducing DirectX, Chapter Four: Arrays, Pointers and Strings, Chapter Five: Object-Oriented Design, Appendices.

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Book SynopsisGenerating functions, one of the most important tools in enumerative combinatorics, are a bridge between discrete mathematics and continuous analysis. Generating functions have numerous applications in mathematics, especially in - Combinatorics - Probability Theory - Statistics - Theory of Markov Chains - Number Theory One of the most important and relevant recent applications of combinatorics lies in the development of Internet search engines whose incredible capabilities dazzle even the mathematically trained user.Trade Review" ""Wilf's writing is clear and friendly; his exorcises are instructive and plentiful... This book is valuable reading for even the best of specialists..."" -E. Rodney Canfield, The Mathematical Intelligencer , March 1993 ""This is a first rate, carefully planned and executed book written by a 'black belt gereratingfunctionologist.' I'll be using it the next time I teach..."" -George Andrews, SIAM News, October 1994 ""Wilf's book is very well-written and easy to read by any serious mathematics student. Scientists in other disciplines often encounter the need to study sequences that naturally arise in their own discipline. The book is well-suited fo them, too."" -Short Book Reviews, January 2006"Table of ContentsIntroductory Ideas and Examples. Series. Cards, Decks and Hands: The Exponential Formula. Applications of Generating Functions. Analytic and Asymptotic Models. Appendix: Using Maple and Mathematica Solutions. References.

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