Computer networking and communications Books

Book SynopsisThe Wireless Metropolitan Area Network (WirelessMAN) is a promising Broadband Wireless Access (BWA) technology that provides high-speed, high-bandwidth efficiency and high-capacity multimedia services for both residential and enterprise applications. Mobile WiMAX: Toward Broadband Wireless Metropolitan Area Networks examines the basic concepts, recent advances, and latest standard specifications pertinent to WirelessMANs, placing emphasis on IEEE 802.16-based WiMAX. After introducing the basics of WirelessMAN, the book addresses topics in three accessible parts. The first part focuses on radio frequency (RF), signal processing, multiple in-multiple out (MIMO) technology, and identifying challenges and possible solutions in the physical layer. An examination of protocol issues follows, including those involving medium access control (MAC), quality of service (QoS) in point-to-multi-point (PMP) and mesh networks, cross layer optimization, mobility management, handoff in heterogeneousTable of ContentsIEEE 802.16-Based WirelessMAN. RF System and Circuit Challenges for WiMAX. WirelessMAN Physical Layer Specifications: Signal Processing Perspective. MIMO for WirelessMAN. MIMO Spectral Efficiency of the Mobile WiMAX Downlink. Medium Access Control in WirelessMAN. QoS Services Provisioning at MAC Layer in WiMax Systems. Radio Resource Management in IEEE 802.16 WiMAX Mesh Networks. Cross-Layer Design in WirelessMAN. Mobility Management in Mobile WiMAX. Dynamic Network Selection in Wireless LAN/MAN Heterogeneous Networks. Mobility Support for Wireless PANs, LANs, and MANs. Energy Management in the IEEE 802.16e WirelessMAN. Link Adaptation Mechanisms in WirelessMAN. Analysis of Threats to WiMax/802.16 Security. Techno-Economic Analysis of Fixed WiMAX Networks. Capacity of OFDMA-Based WirelessMAN.

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Book SynopsisWireless mesh networking is a new technology that has the potential to revolutionize how we access the Internet and communicate with co-workers and friends. Wireless Mesh Networks examines the concept and explores its advantages over existing technologies. This book explores existing and future applications, and examines how some of the networking protocols operate.The text offers a detailed analysis of the significant problems affecting wireless mesh networking, including network scale issues, security, and radio frequency interference, and suggests actual and potential solutions for each problem.Although the book's primary focus is the potential use of wireless mesh networks in the commercial marketplace, it enables readers to gain an appreciation for use of the technology in the office, at government agencies, on campus, and in the home.Table of ContentsIntroduction to wireless mesh networking. Radio frequency utilization. Mesh network components. Routing protocols. Network operation. Creating a HotPoint-based mesh network. Wireless mesh standards. The future of wireless mesh networking.

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Book SynopsisIn the NGN world, no truer words are spoken than the future is now. And the competition in the information networking arena will only intensify in the next 5-10 years. Choosing the correct NGN-VAS strategy now will set your company apart. Value Added Services for Next Generation Networks examines the quest for the real added value in modern communication systems. The author covers more than just the technology itself, but also examines how it is being used and how it could be used to gain a strategic advantage. The book starts with a SOTW analysis for PSTN/GSM operators and new entrants and the threats they will undoubtedly face. The author examines the fundamentals of genuine communication services and the service providers'' starting position, then takes you on a tour through the landscape of NGN standards, contrasting the 3GPP IMS architecture with that of IETF, UMA, and OMA. He discusses practical ways to build an NGN SDP and the essential business aspects involved in this Table of ContentsA SWOT Analysis for Fixed, Mobile Operators, and New Entrants in the Voice Market. Review of the Standardization Work for Next Generation Networks. Charging and Rating Requirements for NGN Services. Interconnecting the NGN to Existing PSTN/GSM/CDMA Networks & Systems. The Technical Requirements for Any Modern VAS Platform. A New Generation of Value Added Services. Future Digital Life.

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Book SynopsisService-oriented architecture (SOA) uses services as the baseline for developing new architectures and applications, as networks are built specifically to satisfy service requirements. Most services are currently handled over different networks, but newer services will soon require cross-network support. Architecting the Telecommunication Evolution: Toward Converged Network Services outlines the challenges of providing crossover services and the new architectures and protocols that will enable convergence between circuit- and packet-switched networks.Taking a standards-based approach to converged services, this book lays a foundation for SOA in telecommunications. The authors begin by outlining the development of Internet telephony, focusing on how to use the respective benefits of the traditional public switched telephone network (PSTN) and the Internet to create and implement more value-added services. These two eminent specialists first examine services that originate in Trade Review"Evolving from the current PSTN to Internet Telephony is not an easy task. … The two authors [of this book] are uniquely qualified to explain how this evolution can be architected. … Both authors have used their unique expertise to produce this very first book on the topic."-From the Foreword by Roch Glitho, Ph.D., Editor-in-Chief, IEEE Communications Magazine, 2003-2005Table of ContentsIntroduction. Internet Telephony: The Evolution of a Service-Oriented Architecture. Background: Providing Telephony Service. Comparative Analysis of Signaling Protocols. Crossover Services Origination on the Internet. Crossover Services Originating on the Public Switched Telephone Network. Smart Spaces in the Telecommunications Domain. Conclusions. Appendices. Index.

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Book SynopsisThis book explores the history of hypertext, an influential concept that forms the underlying structure of the World Wide Web and innumerable software applications.Trade Review‘“Memory Machines” will appeal to anyone who is curious about the history of computing in general and hypertext in particular. This book is highly recommended for computer science students and for students of history of science and technology, as well as for computing and engineering enthusiasts.’ —Stephanie Wical, Online Information Review‘[A] richly layered account, focusing on oral histories as much as an analysis of documents. […] This volume provides a sophisticated and vital history of early computing, usefully exploring conceptual ideas around hypertext, outlining the constraints on pioneering efforts to implement models of hypertext as technical prototypes, and ultimately demonstrating how these collectively shaped all subsequent efforts to develop computer-based prototypes for information structuring and retrieval.’ —Craig Hight, ‘Media International Australia’Table of ContentsForeword: To Mandelbrot in Heaven – Stuart Moulthrop; Preface; Chapter 1: Technical Evolution; Chapter 2: Memex as an Image of Potentiality; Chapter 3: Augmenting the Intellect: NLS; Chapter 4. The Magical Place of Literary Memory: Xanadu; Chapter 5: Seeing and Making Connections: HES and FRESS; Chapter 6: Machine-Enhanced (Re)minding: The Development of Storyspace; Conclusion; Notes; Bibliography; Index

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Book SynopsisNet Gain identifies where the next level of value lies on the Internet and lays out the first economic model to quantify the revenue potential and the investment required to build a successful virtual community. From the offerings of commercial online services such as the Motley Fool Investment group to Internet communities of book lovers, Net Gain offers a multitude of real-world scenarios and lessons for building value and creating competitive edge. The authors clearly show that in order to compete in the online economy, you must establish an entirely new approach to product development, marketing, customer service, and distribution, and rethink your company's relationships to customers, suppliers, and competitors. And they show you how to do it.

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Book SynopsisIn Information Rules, authors Shapiro and Varian reveal that many classic economic concepts can provide the insight and understanding necessary to succeed in the information age. They argue that if managers seriously want to develop effective strategies for competing in the new economy, they must understand the fundamental economics of information technology. Whether information takes the form of software code or recorded music, is published in a book or magazine, or even posted on a website, managers must know how to evaluate the consequences of pricing, protecting, and planning new versions of information products, services, and systems. The first book to distill the economics of information and networks into practical business strategies, Information Rules is a guide to the winning moves that can help business leaders navigate successfully through the tough decisions of the information economy.Table of Contents1 The Information Economy 2 Pricing Information 3 Versioning Information 4 Rights Management 5 Recognizing Lock-In 6 Managing Lock-In 7 Networks and Positive Feedback 8 Cooperation and Compatibility 9 Waging a Standards War 10 Information Policy

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Book SynopsisDesigned for upper undergraduate and graduate courses on adversarial learning and AI security, this textbook connects theory with practice using real-world examples, case studies, and hands-on student projects.Trade Review'This textbook is one of the first major efforts to systematically examine adversarial machine learning. It clearly outlines the most common types of attacks on machine learning/AI, and defenses, with rigorous yet practical discussions. I would highly recommend it to any instructor or machine learning student who seeks to understand how to make machine learning more robust and secure.' Carlee Joe-Wong, Carnegie Mellon University'This is a clear and timely introduction to the vital topic of adversarial learning. As leading international experts, the authors provide an accessible explanation of the foundational principles and then deliver a nuanced and extensive survey of recent attack and defense strategies. Multiple suggested projects allow the book to serve as the core of a graduate course.' Mark Coates, McGill University'Remarkably comprehensive, this book explores the realm of adversarial learning, revealing the vulnerabilities and defenses associated with deep learning. With a mix of theoretical insights and practical projects, the book challenges the misconceptions about the robustness of Deep Neural Networks, offering strategies to fortify them. It is well suited for students and professionals with basic calculus, linear algebra, and probability knowledge, and provides foundational background on deep learning and statistical modeling. A must-read for practitioners in the machine learning field, this book is a good guide to understanding adversarial learning, the evolving landscape of defenses, and attacks.' Ferdinando Fioretto, Syracuse University'In a field that is moving at break-neck speed, this book provides a strong foundation for anyone interested in joining the fray.' Amir Rahmati, Stony BrookTable of ContentsContents; Preface; Notation; 1. Overview of adversarial learning; 2. Deep learning background; 3. Basics of detection and mixture models; 4. Test-time evasion attacks (adversarial inputs); 5. Backdoors and before/during training defenses; 6. Post-training reverse-engineering defense (PT-RED) Against Imperceptible Backdoors; 7. Post-training reverse-engineering defense (PT-RED) against patch-incorporated backdoors; 8. Transfer post-training reverse-engineering defense (T-PT-RED) against backdoors; 9. Universal post-training backdoor defenses; 10. Test-time detection of backdoor triggers; 11. Backdoors for 3D point cloud (PC) classifiers; 12. Robust deep regression and active learning; 13. Error generic data poisoning defense; 14. Reverse-engineering attacks (REAs) on classifiers; Appendix. Support Vector Machines (SVMs); References; Index.

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Book SynopsisUtilising both key mathematical tools and state-of-the-art research results, this text explores the principles underpinning large-scale information processing over networks and examines the crucial interaction between big data and its associated communication, social and biological networks. Written by experts in the diverse fields of machine learning, optimisation, statistics, signal processing, networking, communications, sociology and biology, this book employs two complementary approaches: first analysing how the underlying network constrains the upper-layer of collaborative big data processing, and second, examining how big data processing may boost performance in various networks. Unifying the broad scope of the book is the rigorous mathematical treatment of the subjects, which is enriched by in-depth discussion of future directions and numerous open-ended problems that conclude each chapter. Readers will be able to master the fundamental principles for dealing with big data overTable of ContentsPart I. Mathematical Foundations: 1. Tensor models – solution methods and applications Shiqian Ma, Bo Jiang, Xiuzhen Huang and Shuzhong Zhang; 2. Sparsity-aware distributed learning Symeon Chouvardas, Yannis Kopsinis and Sergios Theodoridis; 3. Optimization algorithms for big data with application in wireless networks Mingyi Hong, Wei-Cheng Liao, Ruoyu Sun and Zhi-Quan Luo; 4. A unified distributed algorithm for non-cooperative games Jong-Shi Pang and Meisam Razaviyayn; Part II. Big Data over Cyber Networks: 5. Big data analytics systems Ganesh Ananthanarayanan and Ishai Menache; 6. Distributed big data storage in optical wireless networks Chen Gong, Zhengyuan Xu and Xiaodong Wang; 7. Big data aware wireless communication – challenges and opportunities Suzhi Bi, Rui Zhang, Zhi Ding and Shuguang Cui; 8. Big data processing for smart grid security Lanchao Liu, Zhu Han, H. Vincent Poor and Shuguang Cui; Part III. Big Data over Social Networks: 9. Big data: a new perspective on cities Riccardo Gallotti, Thomas Louail, Rémi Louf and Marc Barthelemy; 10. High dimensional network analytics: mapping topic networks in Twitter data during the Arab Spring Kathleen M. Carley, Wei Wei and Kenneth Joseph; 11. Social influence analysis in the big data era – a review Jianping Cao, Dongliang Duan, Liuqing Yang, Qingpeng Zhang, Senzhang Wang and Feiyue Wang; Part IV. Big Data over Biological Networks: 12. Inference of gene regulatory networks – validation and uncertainty Xiaoning Qian, Byung-Jun Yoon and Edward R Dougherty; 13. Inference of gene networks associated with the host response to infectious disease Zhe Gan, Xin Yuan, Ricardo Henao, Ephraim L. Tsalik and Lawrence Carin; 14. Gene-set-based inference of biological network topologies from big molecular profiling data Lipi Acharya and Dongxiao Zhu; 15. Large scale correlation mining for biomolecular network discovery Alfred Hero and Bala Rajaratnam.

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Book SynopsisDiscover this multi-disciplinary and insightful work, which integrates machine learning, edge computing, and big data. Presents the basics of training machine learning models, key challenges and issues, as well as comprehensive techniques including edge learning algorithms, and system design issues. Describes architectures, frameworks, and key technologies for learning performance, security, and privacy, as well as incentive issues in training/inference at the network edge. Intended to stimulate fruitful discussions, inspire further research ideas, and inform readers from both academia and industry backgrounds. Essential reading for experienced researchers and developers, or for those who are just entering the field.Table of Contents1. Introduction; 2. Preliminary; 3. Fundamental Theory and Algorithms of Edge Learning; 4. Communication-Efficient Edge Learning; 5. Computation Acceleration; 6. Efficient Training with Heterogeneous Data Distribution; 7. Security and Privacy Issues in Edge Learning Systems; 8. Edge Learning Architecture Design for System Scalability; 9. Incentive Mechanisms in Edge Learning Systems; 10. Edge Learning Applications.

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Book SynopsisWindows security concepts and technologies for IT beginners IT security can be a complex topic, especially for those new to the field of IT.Table of ContentsIntroduction. Chapter 1 Understanding Core Security Principles. Chapter 2 Understanding Malware and Social Engineering. Chapter 3 Understanding User Authentication. Chapter 4 Securing Access with Permissions. Chapter 5 Using Audit Policies and Network Auditing. Chapter 6 Protecting Clients and Servers. Chapter 7 Protecting a Network. Chapter 8 Understanding Wireless Security. Chapter 9 Understanding Physical Security. Chapter 10 Enforcing Confidentiality with Encryption. Chapter 11 Understanding Certificates and a PKI. Chapter 12 Understanding Internet Explorer Security. Appendix A Answers to Review Questions. Appendix B Microsoft's Certification Program. Index.

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Book SynopsisThe core concepts and technologies of Windows networking Networking can be a complex topic, especially for those new to the field of IT.Table of ContentsIntroduction xix Chapter 1 Introduction to Networking 1 Comparing Logical and Physical Networks 1 Networking Home Computers 2 Networking Small Offices and Home Offices 4 Understanding Local Area Networks 6 Comparing Workgroups and Domains 7 Exploring the Benefits of Domains and Domain Controllers 9 Networking Large Offices 10 Networking Enterprises 12 Understanding Wide Area Networks 12 Understanding Branch Offices 13 Accessing Networks Remotely 14 Understanding Standards Organizations 15 Understanding the Internet Engineering Task Force 16 Understanding the World Wide Web Consortium 17 Understanding the Institute of Electrical and Electronics Engineers 18 Understanding the International Telecommunication Union 18 The Essentials and Beyond 18 Chapter 2 Overview of Networking Components 21 Comparing Unicast, Broadcast, and Multicast Traffic 21 Understanding Unicast Traffic 22 Understanding Broadcast Traffic 23 Understanding Multicast Traffic 25 Understanding Network Hardware 26 Understanding Hubs 27 Understanding Switches 28 Understanding Bridges 29 Understanding Routers 30 Understanding Firewalls 32 Understanding Media 34 Exploring Protocols and Services 36 Exploring Protocols 36 Understanding Services 37 Understanding Basic Topologies 38 The Essentials and Beyond 39 Chapter 3 Understanding the OSI Model 41 Understanding the OSI Model 41 Application Layer 43 Presentation Layer 44 Session Layer 45 Transport Layer 46 Network Layer 48 Data Link Layer 49 Physical Layer 52 Putting It Together 52 Packets and Frames 53 Understanding the TCP/IP Model 55 Mapping Devices on the OSI and TCP Models 56 Physical Layer 58 Data Link Layer 59 Network Layer 59 Application Layer 60 Mapping Protocols on the OSI and TCP/IP Models 60 The Essentials and Beyond 61 Chapter 4 Core TCP/IP Protocols 63 Understanding TCP and UDP 63 Exploring TCP 64 Exploring UDP 66 Exploring Common Protocols 67 Address Resolution Protocol 67 Hypertext Transfer Protocol 68 File Transfer Protocol 69 Trivial File Transfer Protocol 71 Telnet 71 Remote Desktop Services 71 Secure Sockets Layer 72 Transport Layer Security 72 Secure Shell 73 Internet Protocol Security 74 Simple Mail Transfer Protocol 74 Post Office Protocol v3 75 Internet Message Access Protocol 75 Lightweight Directory Access Protocol 76 Kerberos 77 Point-to-Point Tunneling Protocol 77 Layer 2 Tunneling Protocol 77 Simple Network Management Protocol 78 Internet Group Multicast Protocol 78 Internet Control Message Protocol 78 Understanding Ports 79 Controlling Port Traffic with a Firewall 81 Mapping Internally Used Ports and Protocols 81 The Essentials and Beyond 83 Chapter 5 Exploring IPv4 85 Exploring the Components of an IPv4 Address 85 Ascertaining the Network ID and Host ID of an IP Address 86 Identifying the Default Gateway 90 Determining Local and Remote Addresses 91 Understanding Classful IP Addresses 92 Identifying Reserved IP Address Ranges 94 Exploring an IPv4 Address in Binary 95 Understanding the Bits of an IP Address 95 Understanding CIDR Notation 98 Masking the IP Address 98 Using Classless IP Addresses 100 Subnetting IPv4 Addresses 100 Determining the Number of Subnet Bits 101 Determining the Number of Hosts in a Network 103 Identifying Local and Remote Addresses 105 Applying Subnetting Knowledge 107 Comparing Manual and Automatic Assignment of IPv4 Addresses 110 Manually Configuring IPv4 110 Using DHCP 110 Understanding APIPA 112 The Essentials and Beyond 113 Chapter 6 Exploring IPv6 117 Exploring IPv6 Addresses 117 Comparing IPv4 Classes and IPv6 Prefixes 118 Understanding Hexadecimal 119 Displaying IPv6 Addresses 120 Comparing IPv6 Transmission Types 121 Understanding the Need for IPv6 122 Understanding Neighbor Discovery 122 Exploring the Components of an IPv6 Address 123 Understanding Global Unicast Addresses 124 Understanding Link-Local Addresses 125 Understanding Unique Local Addresses 126 Understanding the Dual IP Stack 127 Using IPv4-Mapped IPv6 Addresses 127 Understanding IPv4 to IPv6 Tunneling Protocols 128 Comparing Manual and Automatic Assignment of IPv6 129 Manually Configuring IPv6 129 Using DHCPv6 130 The Essentials and Beyond 131 Chapter 7 Connecting Computers to a Network 133 Identifying Potential Problems with Connectivity 133 Understanding EMI 134 Understanding RFI 134 Avoiding Power Spikes 134 Avoiding Interception 137 Preventing Fire Hazards 142 Understanding Cross Talk 142 Exploring Cable Types and Their Characteristics 144 Understanding Twisted Pair 144 Comparing Unshielded and Shielded Twisted Pair 146 Comparing Straight-Through and Crossover Cables 146 Understanding Fiber Optic 147 Understanding Wireless 149 The Essentials and Beyond 150 Chapter 8 Networking Computers with Switches 153 Connecting Multiple Computers 153 Understanding Physical Ports 156 Identifying the Number and Type of Ports 156 Identifying Ports in Drawings 157 Comparing Hubs and Switches 158 Understanding Collision Domains 159 Identifying a Collision Domain with a Hub 159 Identifying Collision Domains with a Switch 160 Mapping Ports to MAC Addresses 161 Comparing Managed and Unmanaged Switches 162 Understanding Unmanaged Switches 163 Understanding Managed Switches 163 Comparing Layer 2 and Layer 3 Switches 164 Using a Managed Switch to Create a VLAN 164 Exploring Switch Speeds 167 Identifying Transmission Speeds 168 Understanding the Uplink Port 169 Identifying Backplane Speed 170 Understanding Security Options 170 Understanding Port Security 171 Planning Hardware Redundancy 171 The Essentials and Beyond 172 Chapter 9 Connecting Networks with Routers 175 Connecting Multiple Networks 175 Comparing Hardware Routers and Software Routers 177 Understanding Default Routes 177 Understanding Directly Connected Routes 179 Routing Traffic on a Network 180 Creating Static Routes 180 Configuring Dynamic Routing 182 Understanding the Routing Table185 Identifying Transmission Speeds 187 Routing Software in Windows Server 2008 188 Adding Routing Services to Windows Server 2008 188 Configuring a Router on Windows Server 2008 190 Understanding Other Routing Protocols 192 Using a DHCP Relay Agent 193 Using an IGMP Router and Proxy 194 Using NAT 195 The Essentials and Beyond 195 Chapter 10 Resolving Names to IP Addresses 197 Exploring Types of Names Used in Networks 197 Understanding Host Names 199 Understanding NetBIOS Names 199 Creating NetBIOS Names from Host Names 202 Viewing and Modifying a Computer Name 203 Exploring Types of Name Resolution 204 Understanding Domain Naming Service 205 Viewing the Host Cache 210 Viewing the Hosts File 211 Understanding WINS 212 Viewing the NetBIOS Cache 213 Understanding the Lmhosts File 214 Understanding Broadcast Name Resolution 214 Understanding Link-Local Multicast Name Resolution 214 Identifying the Steps in Name Resolution 215 Identifying Steps in Host Name Resolution 215 Identifying Steps in NetBIOS Name Resolution 216 The Essentials and Beyond 217 Chapter 11 Understanding Network Security Zones 219 Understanding Risks on the Internet 219 Exploring an Intranet 221 Understanding Network Address Translation 222 Understanding Proxy Servers 224 Understanding Firewalls 227 Exploring the Windows Server 2008 Firewall 229 Identifying a Perimeter Network 232 Understanding a Reverse Proxy Server 233 Understanding Guest Networks 234 Understanding Extranets 235 The Essentials and Beyond 236 Chapter 12 Understanding Wireless Networking 239 Exploring Basic Wireless Components 239 Using Wireless Access Points 240 Naming the Wireless Network 241 Comparing CSMA/CD and CSMA/CA 243 Comparing Networking Standards and Characteristics 243 Comparing FHSS, DSSS, and OFDM 244 IEEE 802 11 245 IEEE 802 11a 246 IEEE 802 11b 247 IEEE 802 11g 247 IEEE 802 11n 248 Comparing Network Security Methods 248 Wired Equivalent Privacy 249 Wi-Fi Protected Access 251 WPA2 252 Using an IEEE 802 1x Authentication Server 253 Using Wireless Networks 254 Home Wireless Networks 255 Wireless Networks in a Business 258 Understanding Point-to-Point Wireless 259 The Essentials and Beyond 261 Chapter 13 Understanding Internet Access Methods and Wide Area Networks 263 Comparing Connectivity Methods Used in Homes and SOHOs 263 Using a Dial-up Connection 264 Connecting with DSL 265 Employing Broadband Cable 266 Connecting via Satellite 267 Comparing Connectivity Methods in Enterprises 269 Exploring Digital Signal Lines 271 Using ISDN 271 Using T1/T3 Lines and E1/E3 Lines 272 Ethernet WAN 273 Exploring Remote Access Services 273 Connecting to RAS via Dial-up 274 Connecting to RAS via a VPN 276 Comparing Client VPNs with Gateway VPNs 278 Adding Remote Access Services to Windows Server 2008 278 Using RADIUS 279 The Essentials and Beyond 280 Chapter 14 Troubleshooting TCP/IP 283 Using the Command Prompt 283 Getting Help at the Command Prompt 284 Using Switches 285 Understanding Case Sensitivity 285 Checking the TCP/IP Configuration with ipconfig 287 Troubleshooting Connectivity with ping 291 Identifying Routers with tracert 295 Verifying the Routed Path with pathping 297 Viewing TCP/IP Statistics with netstat 299 Installing Telnet 304 The Essentials and Beyond 306 Appendix A Answers to Review Questions 309 Chapter 1 309 Chapter 2 310 Chapter 3 310 Chapter 4 311 Chapter 5 312 Chapter 6 312 Chapter 7 313 Chapter 8 314 Chapter 9 314 Chapter 10 315 Chapter 11 316 Chapter 12 316 Chapter 13 317 Chapter 14 317 Appendix B Microsoft’s Certification Program 319 Certification Objectives Map 320 Index 325

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Book SynopsisWhile geographic redundancy can obviously be a huge benefit for disaster recovery, it is far less obvious what benefit is feasible and likely for more typical non-catastrophic hardware, software, and human failures. Georedundancy and Service Availability provides both a theoretical and practical treatment of the feasible and likely benefits of geographic redundancy for both service availability and service reliability. The text provides network/system planners, IS/IT operations folks, system architects, system engineers, developers, testers, and other industry practitioners with a general discussion about the capital expense/operating expense tradeoff that frames system redundancy and georedundancy.Table of ContentsFigures xv Tables xix Equations xxi Preface and Acknowledgments xxiii Audience xxiv Organization xxiv Acknowledgments xxvi PART 1 BASICS 1 1 SERVICE, RISK, AND BUSINESS CONTINUITY 3 1.1 Service Criticality and Availability Expectations 3 1.2 The Eight-Ingredient Model 4 1.3 Catastrophic Failures and Geographic Redundancy 7 1.4 Geographically Separated Recovery Site 11 1.5 Managing Risk 12 1.6 Business Continuity Planning 14 1.7 Disaster Recovery Planning 15 1.8 Human Factors 17 1.9 Recovery Objectives 17 1.10 Disaster Recovery Strategies 18 2 SERVICE AVAILABILITY AND SERVICE RELIABILITY 20 2.1 Availability and Reliability 20 2.2 Measuring Service Availability 25 2.3 Measuring Service Reliability 33 PART 2 MODELING AND ANALYSIS OF REDUNDANCY 35 3 UNDERSTANDING REDUNDANCY 37 3.1 Types of Redundancy 37 3.2 Modeling Availability of Internal Redundancy 44 3.3 Evaluating High-Availability Mechanisms 52 4 OVERVIEW OF EXTERNAL REDUNDANCY 59 4.1 Generic External Redundancy Model 59 4.2 Technical Distinctions between Georedundancy and Co-Located Redundancy 74 4.3 Manual Graceful Switchover and Switchback 75 5 EXTERNAL REDUNDANCY STRATEGY OPTIONS 77 5.1 Redundancy Strategies 77 5.2 Data Recovery Strategies 79 5.3 External Recovery Strategies 80 5.4 Manually Controlled Recovery 81 5.5 System-Driven Recovery 83 5.6 Client-Initiated Recovery 85 6 MODELING SERVICE AVAILABILITY WITH EXTERNAL SYSTEM REDUNDANCY 98 6.1 The Simplistic Answer 98 6.2 Framing Service Availability of Standalone Systems 99 6.3 Generic Markov Availability Model of Georedundant Recovery 103 6.4 Solving the Generic Georedundancy Model 115 6.5 Practical Modeling of Georedundancy 121 6.6 Estimating Availability Benefit for Planned Activities 130 6.7 Estimating Availability Benefit for Disasters 131 7 UNDERSTANDING RECOVERY TIMING PARAMETERS 133 7.1 Detecting Implicit Failures 134 7.2 Understanding and Optimizing RTO 141 8 CASE STUDY OF CLIENT-INITIATED RECOVERY 147 8.1 Overview of DNS 147 8.2 Mapping DNS onto Practical Client-Initiated Recovery Model 148 8.3 Estimating Input Parameters 154 8.4 Predicted Results 165 8.5 Discussion of Predicted Results 172 9 SOLUTION AND CLUSTER RECOVERY 174 9.1 Understanding Solutions 174 9.2 Estimating Solution Availability 177 9.3 Cluster versus Element Recovery 179 9.4 Element Failure and Cluster Recovery Case Study 182 9.5 Comparing Element and Cluster Recovery 186 9.6 Modeling Cluster Recovery 187 PART 3 RECOMMENDATIONS 201 10 GEOREDUNDANCY STRATEGY 203 10.1 Why Support Multiple Sites? 203 10.2 Recovery Realms 204 10.3 Recovery Strategies 206 10.4 Limp-Along Architectures 207 10.5 Site Redundancy Options 208 10.6 Virtualization, Cloud Computing, and Standby Sites 216 10.7 Recommended Design Methodology 217 11 MAXIMIZING SERVICE AVAILABILITY VIA GEOREDUNDANCY 219 11.1 Theoretically Optimal External Redundancy 219 11.2 Practically Optimal Recovery Strategies 220 11.3 Other Considerations 228 12 GEOREDUNDANCY REQUIREMENTS 230 12.1 Internal Redundancy Requirements 230 12.2 External Redundancy Requirements 233 12.3 Manually Controlled Redundancy Requirements 235 12.4 Automatic External Recovery Requirements 237 12.5 Operational Requirements 242 13 GEOREDUNDANCY TESTING 243 13.1 Georedundancy Testing Strategy 243 13.2 Test Cases for External Redundancy 246 13.3 Verifying Georedundancy Requirements 247 13.4 Summary 254 14 SOLUTION GEOREDUNDANCY CASE STUDY 256 14.1 The Hypothetical Solution 256 14.2 Standalone Solution Analysis 259 14.3 Georedundant Solution Analysis 263 14.4 Availability of the Georedundant Solution 269 14.5 Requirements of Hypothetical Solution 269 14.6 Testing of Hypothetical Solution 277 Summary 285 Appendix: Markov Modeling of Service Availability 292 Acronyms 296 References 298 About the Authors 300 Index 302

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Book SynopsisCovering internet security, malware, phishing, and how to combat these serious and growing issues on both desktop and smart phone platforms, this book draws upon state-of-the-art research from industry and academia. The content also describes proven countermeasures using real world examples.Trade Review“For those looking for a book to gain situation awareness about the dangers of the Internet, one is hard pressed to find a better title than The Death of the Internet.” (Word Virus, 17 April 2013) “For those looking for a book to gain situation awareness about the dangers of the Internet, one is hard pressed to find a better title than The Death of the Internet.” (Slashdot, 15 April 2013) “The book includes possible solutions to some of the problems, but the overwhelming appeal of this text is the awareness is provides. Summing Up: Highly recommended. Students of all levels, general readers, and professionals/practitioners.” (Choice, 1 January 2012) Table of ContentsForeword xv Preface xvii Is the Title of this Book a Joke? xix Acknowledgments xxi Contributors xxiii Part I The Problem 1 What Could Kill the Internet? And so What? 3 2 It is About People 7 2.1 Human and Social Issues 7 Markus Jakobsson 2.1.1 Nigerian Scams 8 2.1.2 Password Reuse 9 2.1.3 Phishing 11 2.2 Who are the Criminals? 13 Igor Bulavko 2.2.1 Who are they? 13 2.2.2 Where are they? 14 2.2.3 Deep-Dive: Taking a Look at Ex-Soviet Hackers 14 2.2.4 Let’s try to Find Parallels in the World we Live in 16 2.2.5 Crime and Punishment? 16 3 How Criminals Profit 19 3.1 Online Advertising Fraud 20 Nevena Vratonjic, Mohammad Hossein Manshaei, and Jean-Pierre Hubaux 3.1.1 Advertising on the Internet 20 3.1.2 Exploits of Online Advertising Systems 23 3.1.3 Click Fraud 25 3.1.4 Malvertising: Spreading Malware via Ads 31 3.1.5 Inflight Modification of Ad Traffic 32 3.1.6 Adware: Unsolicited Software Ads 34 3.1.7 Conclusion 35 3.2 Toeing the Line: Legal but Deceptive Service Offers 35 Markus Jakobsson and Ruilin Zhu 3.2.1 How Does it Work? 36 3.2.2 What do they Earn? 36 3.3 Phishing and Some Related Attacks 38 Markus Jakobsson and William Leddy 3.3.1 The Problem is the User 38 3.3.2 Phishing 38 3.3.3 Man-in-the-Middle 39 3.3.4 Man-in-the-Browser 40 3.3.5 New Attack: Man-in-the-Screen 41 3.4 Malware: Current Outlook 42 Members of the BITS Security Working Group and staff leads Greg Rattray and Andrew Kennedy 3.4.1 Malware Evolution 42 3.4.2 Malware Supply and Demand 48 3.5 Monetization 53 Markus Jakobsson 3.5.1 There is Money Everywhere 53 4 How ThingsWork and Fail 57 4.1 Online Advertising: With Secret Security 58 Markus Jakobsson 4.1.1 What is a Click? 58 4.1.2 How Secret Filters are Evaluated 60 4.1.3 What do Fraudsters Know? 62 4.2 Web Security Remediation Efforts 63 Jeff Hodges and Andy Steingruebl 4.2.1 Introduction 63 4.2.2 The Multitude of Web Browser Security Mechanisms 64 4.2.3 Where do we go from Here? 75 4.3 Content-Sniffing XSS Attacks: XSS with Non-HTML Content 75 Juan Caballero, Adam Barth, and Dawn Song 4.3.1 Introduction 75 4.3.2 Content-Sniffing XSS Attacks 77 4.3.3 Defenses 84 4.3.4 Conclusion 89 4.4 Our Internet Infrastructure at Risk 89 Garth Bruen 4.4.1 Introduction 89 4.4.2 The Political Structure 90 4.4.3 The Domain 92 4.4.4 WHOIS: Ownership and Technical Records 94 4.4.5 Registrars: Sponsors of Domain Names 96 4.4.6 Registries: Sponsors of Domain Extensions 97 4.4.7 CCTLDs: The Sovereign Domain Extensions 99 4.4.8 ICANN: The Main Internet Policy Body 100 4.4.9 Conclusion 102 4.5 Social Spam 103 Dimitar Nikolov and Filippo Menczer 4.5.1 Introduction 103 4.5.2 Motivations for Spammers 105 4.5.3 Case Study: Spam in the GiveALink Bookmarking System 108 4.5.4 Web Pollution 114 4.5.5 The Changing Nature of Social Spam: Content Farms 116 4.5.6 Conclusion 117 4.6 Understanding CAPTCHAs and Their Weaknesses 117 Elie Bursztein 4.6.1 What is a Captcha? 117 4.6.2 Types of Captchas 118 4.6.3 Evaluating Captcha Attack Effectiveness 118 4.6.4 Design of Captchas 119 4.6.5 Automated Attacks 124 4.6.6 Crowd-Sourcing: Using Humans to Break Captchas 127 4.7 Security Questions 131 Ariel Rabkin 4.7.1 Overview 131 4.7.2 Vulnerabilities 134 4.7.3 Variants and Possible Defenses 138 4.7.4 Conclusion 139 4.8 Folk Models of Home Computer Security 140 Rick Wash and Emilee Rader 4.8.1 The Relationship Between Folk Models and Security 140 4.8.2 Folk Models of Viruses and Other Malware 142 4.8.3 Folk Models of Hackers and Break-Ins 146 4.8.4 Following Security Advice 149 4.8.5 Lessons Learned 153 4.9 Detecting and Defeating Interception Attacks Against SSL 154 Christopher Soghoian and Sid Stamm 4.9.1 Introduction 154 4.9.2 Certificate Authorities and the Browser Vendors 155 4.9.3 Big Brother in the Browser 157 4.9.4 Compelled Assistance 158 4.9.5 Surveillance Appliances 159 4.9.6 Protecting Users 160 4.9.7 Threat Model Analysis 163 4.9.8 Related Work 166 4.9.9 Conclusion 168 5 The Mobile Problem 169 5.1 Phishing on Mobile Devices 169 Adrienne Porter Felt and David Wagner 5.1.1 The Mobile Phishing Threat 170 5.1.2 Common Control Transfers 172 5.1.3 Phishing Attacks 178 5.1.4 Web Sender⇒Mobile Target 182 5.1.5 Web Sender⇒Web Target 184 5.1.6 Attack Prevention 185 5.2 Why Mobile Malware will Explode 185 Markus Jakobsson and Mark Grandcolas 5.2.1 Nineteen Eighty-Six: When it all Started 186 5.2.2 A Glimpse of Users 186 5.2.3 Why Market Size Matters 186 5.2.4 Financial Trends 187 5.2.5 Mobile Malware Outlook 187 5.3 Tapjacking: Stealing Clicks on Mobile Devices 189 Gustav Rydstedt, Baptiste Gourdin, Elie Bursztein, and Dan Boneh 5.3.1 Framing Attacks 189 5.3.2 Phone Tapjacking 191 5.3.3 Framing Facebook 194 5.3.4 Summary and Recommendations 195 6 The Internet and the PhysicalWorld 197 6.1 Malware-Enabled Wireless Tracking Networks 197 Nathaniel Husted and Steven Myers 6.1.1 Introduction 198 6.1.2 The Anatomy of a Modern Smartphone 199 6.1.3 Mobile Tracking Networks: A Threat to Smartphones 200 6.1.4 Conclusion 219 6.2 Social Networking Leaks 219 Mayank Dhiman and Markus Jakobsson 6.2.1 Introduction 220 6.2.2 Motivations for Using Social Networking Sites 220 6.2.3 Trust and Privacy 221 6.2.4 Known Issues 222 6.2.5 Case Study: Social Networking Leaks in the Physical World 225 6.3 Abuse of Social Media and Political Manipulation 231 Bruno Gon¸calves, Michael Conover, and Filippo Menczer 6.3.1 The Rise of Online Grassroots Political Movements 231 6.3.2 Spam and Astroturfing 232 6.3.3 Deceptive Tactics 233 6.3.4 The Truthy System for Astroturf Detection 236 6.3.5 Discussion 240 Part II Thinking About Solutions 7 Solutions to the Problem 245 7.1 When and How to Authenticate 245 Richard Chow, Elaine Shi, Markus Jakobsson, Philippe Golle, Ryusuke Masuoka, Jesus Molina, Yuan Niu, and Jeff Song 7.1.1 Problem Description 246 7.1.2 Use Cases 247 7.1.3 System Architecture 248 7.1.4 User Privacy 250 7.1.5 Machine Learning/Algorithms 250 7.1.6 User Study 252 7.2 Fastwords: Adapting Passwords to Constrained Keyboards 255 Markus Jakobsson and Ruj Akavipat 7.2.1 The Principles Behind Fastwords 256 7.2.2 Basic Feature Set 258 7.2.3 Extended Feature Set 260 7.2.4 Sample Stories and Frequencies 261 7.2.5 Recall Rates 262 7.2.6 Security Analysis 264 7.2.7 The Security of Passwords 264 7.2.8 Entry Speed 268 7.2.9 Implementation of Fastword Entry 270 7.2.10 Conclusion 271 7.3 Deriving PINs from Passwords 271 Markus Jakobsson and Debin Liu 7.3.1 Introduction 272 7.3.2 A Brief Discussion of Passwords 273 7.3.3 How to Derive PINs from Passwords 274 7.3.4 Analysis of Passwords and Derived PINs 275 7.3.5 Security Analysis 278 7.3.6 Usability Experiments 280 7.4 Visual Preference Authentication 282 Yuan Niu, Markus Jakobsson, Gustav Rydstedt, and Dahn Tamir 7.4.1 Password Resets 282 7.4.2 Security Questions Aren’t so Secure 283 7.4.3 What is Visual Preference-Based Authentication 283 7.4.4 Evaluating Visual Preference-Based Authentication 285 7.4.5 Case Study: Visual Blue Moon Authentication 286 7.4.6 Conclusion 290 7.5 The Deadly Sins of Security User Interfaces 290 Nathan Good 7.5.1 Security Applications with Frustrating User Interfaces 291 7.5.2 The Four Sins of Security Application User Interfaces 293 7.5.3 Consumer Choice: A Security Bugbear 293 7.5.4 Security by Verbosity 299 7.5.5 Walls of Checkboxes 300 7.5.6 All or Nothing Switch 302 7.5.7 Conclusion 304 7.6 SpoofKiller—Let’s Kiss Spoofing Goodbye! 304 Markus Jakobsson and William Leddy 7.6.1 A Key to the Solution: Interrupts 305 7.6.2 Why can the User Log in to Good Sites, but not Bad Ones? 305 7.6.3 What About Sites that are Good . . . but not Certified Good? 308 7.6.4 SpoofKiller: Under the Hood 309 7.6.5 Say we Implement SpoofKiller—then What? 311 7.7 Device Identification and Intelligence 312 Ori Eisen 7.7.1 1995–2001: The Early Years of Device Identification 313 7.7.2 2001–2008 Tagless Device Identification Begins 314 7.7.3 2008—Present: Private Browsing and Beyond 319 7.8 How can we Determine if a Device is Infected or not? 323 Aur´elien Francillon, Markus Jakobsson, and Adrian Perrig 7.8.1 Why Detection is Difficult 323 7.8.2 Setting up an Isolated Environment 324 7.8.3 What Could go Wrong? 326 7.8.4 Brief Comparison with TrustZone 328 7.8.5 Summary 328 8 The Future 331 8.1 Security Needs the Best User Experience 332 Hampus Jakobsson 8.1.1 How the User Won Over Features 332 8.1.2 So How Come the iPhone Became so Successful? 332 8.1.3 A World of Information Anywhere 333 8.1.4 Midas’ Touch Screens 334 8.1.5 New Input, New Opportunities 335 8.1.6 Zero-Click and Real-Life User Interfaces 335 8.1.7 Privacy and User Interfaces 336 8.1.8 It all Comes Together 336 8.2 Fraud and the Future 336 Markus Jakobsson References 339 Index 359

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Book SynopsisPraise for ON TOP OF THE CLOUD 21st-century CIOs have a dual responsibility: driving down costs and creating new business value. Managing this seeming dichotomy is the domain of top business executives everywhere, and CIOs everywhere are learning to step it up. The original research contained in Hunter''s book serves as a practical road map for IT strategy in today''s ultra-competitive markets.Randy Spratt, EVP, CIO, and CTO, McKesson Corporation This is a thoughtfully written book, and the timing is perfect. Hunter really understands the challenges confronting transformational CIOs in today''s markets, and he captures the choices they face as they work to create value for their organizations while driving down the costs of doing business in the modern world. The wealth of information contained in this book makes it truly valuable to career IT leaders and future CIOs alike.Mark Polansky, Senior Client Partner and Managing DirectoTrade Review"In his book, On Top of the Cloud Muller interviewed top CIOs about the challenges and opportunities of cloud technology, and how they've learned to lead their companies into a cloud-driven future. These transformational CIOs, as Hunter refers to them, are technology leaders, not followers. They function as champions of innovation and continuous improvement, a role that often requires them to be more like a CEO than CIO." (Monster.com, April 2012)Table of ContentsForeword xi Preface xv Acknowledgments xxiii Introduction xxv A New Business Model xxvii ‘‘Thoughtfully Progressive’’ xxviii Part I: Transformational Leadership 1 Chapter 1 The Rising Tide 3 The CIO as Rock Star 6 Real Stories from Real IT Leaders 7 Learning from Listening 8 More Than Technology 9 The Real Challenge Is Organizational 9 Leadership Is Essential 12 Chapter 2 IT Does Matter 17 Stay Focused on Delivering Value 20 Replacing the Perpetual Pendulum 22 Driving the Innovation Agenda 24 It’s All a Question of Perspective 28 Chapter 3 The Engine of Innovation 31 Bringing Innovation to the Surface 36 Incentivizing Innovation 39 Chapter 4 Finding the Right Balance 45 Winds of Change 49 The Third Bucket 51 The Closer 53 Outside versus Inside 55 Articulating the Value of Technology 57 Chapter 5 The Customer-Focused CIO 61 Top Line or Bottom Line? 65 Driving Business Growth 66 The Rapid Enabler 68 Own, Rent, or Both? 72 Multiple Models 75 Also Consider the User Experience 76 Chapter 6 To Cloud or Not to Cloud 79 Fail Fast, Fail Cheap 83 A Skunk Works in the Cloud 85 Weaving the Seamless Tapestry 87 Part II: Driving Change 91 Chapter 7 In Front of the Firewall 93 Avon Calling 100 When the Model Fits 103 Chapter 8 The New Speed of Change 107 Updating the Mental Model 115 Innovation under Pressure 119 The Cloud on Wheels 121 Campaigning in the Cloud 122 Part III: Building Value 127 Chapter 9 Pushing the Envelope 129 Two Sides of the Same Coin 138 A Multiplicity of Clouds 142 Turn of the Tide 146 Translating ‘‘Speeds and Feeds’’ into Cash Flow 152 Chapter 10 Entering the Cloud 155 Governance Is Fundamental to Success 161 Due Diligence 163 Taking ‘‘No’’ Off the Table 173 Afterword 179 Meet Our Sources 189 Recommended Reading 221 About the Author 225 About HMG Strategy LLC 227 Index 229

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Book SynopsisAn essential how-to guide for experienced DBAs on the most significant product release since 2005! Microsoft SQL Server 2012 will have major changes throughout the SQL Server and will impact how DBAs administer the database.Trade ReviewIf you want a good, wide ranging, general SQL Server 2012 administration book, I can certainly recommend this book. (I Programmer, December 2013)Table of ContentsINTRODUCTION xxxvii CHAPTER 1: SQL SERVER 2012 ARCHITECTURE 1 CHAPTER 2: INSTALLING SQL SERVER 2012 BEST PRACTICES 21 CHAPTER 3: UPGRADING SQL SERVER 2012 BEST PRACTICES 53 CHAPTER 4: MANAGING AND TROUBLESHOOTING THE DATABASE ENGINE 71 CHAPTER 5: AUTOMATING SQL SERVER 105 CHAPTER 6: SERVICE BROKER IN SQL SERVER 2012 147 CHAPTER 7: SQL SERVER CLR INTEGRATION 167 CHAPTER 8: SECURING THE DATABASE INSTANCE 181 CHAPTER 9: CHANGE MANAGEMENT 197 CHAPTER 10: CONFIGURING THE SERVER FOR OPTIMAL PERFORMANCE 233 CHAPTER 11: OPTIMIZING SQL SERVER 2012 273 CHAPTER 12: MONITORING YOUR SQL SERVER 317 CHAPTER 13: PERFORMANCE TUNING T-SQL 399 CHAPTER 14: INDEXING YOUR DATABASE 449 CHAPTER 15: REPLICATION 473 CHAPTER 16: CLUSTERING SQL SERVER 2012 509 CHAPTER 17: BACKUP AND RECOVERY 547 CHAPTER 18: SQL SERVER 2012 LOG SHIPPING 607 CHAPTER 19: DATABASE MIRRORING 641 CHAPTER 20: INTEGRATION SERVICES ADMINISTRATION AND PERFORMANCE TUNING 695 CHAPTER 21: ANALYSIS SERVICES ADMINISTRATION AND PERFORMANCE TUNING 729 CHAPTER 22: SQL SERVER REPORTING SERVICES ADMINISTRATION 765 CHAPTER 23: SQL SERVER 2012 SHAREPOINT 2010 INTEGRATION 815 CHAPTER 24: SQL AZURE ADMINISTRATION AND CONFIGURATION 837 CHAPTER 25: ALWAYSON AVAILABILITY GROUPS 857 INDEX 885

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Book SynopsisLearn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified white box approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical progTable of ContentsPREFACE xxi ACKNOWLEDGMENTS xxix PART I DATA PREPARATION 1 CHAPTER 1 AN INTRODUCTION TO DATA MINING AND PREDICTIVE ANALYTICS 3 1.1 What is Data Mining? What is Predictive Analytics? 3 1.2 Wanted: Data Miners 5 1.3 The Need for Human Direction of Data Mining 6 1.4 The Cross-Industry Standard Process for Data Mining: CRISP-DM 6 1.4.1 CRISP-DM: The Six Phases 7 1.5 Fallacies of Data Mining 9 1.6 What Tasks Can Data Mining Accomplish 10 CHAPTER 2 DATA PREPROCESSING 20 2.1 Why do We Need to Preprocess the Data? 20 2.2 Data Cleaning 21 2.3 Handling Missing Data 22 2.4 Identifying Misclassifications 25 2.5 Graphical Methods for Identifying Outliers 26 2.6 Measures of Center and Spread 27 2.7 Data Transformation 30 2.8 Min–Max Normalization 30 2.9 Z-Score Standardization 31 2.10 Decimal Scaling 32 2.11 Transformations to Achieve Normality 32 2.12 Numerical Methods for Identifying Outliers 38 2.13 Flag Variables 39 2.14 Transforming Categorical Variables into Numerical Variables 40 2.15 Binning Numerical Variables 41 2.16 Reclassifying Categorical Variables 42 2.17 Adding an Index Field 43 2.18 Removing Variables that are not Useful 43 2.19 Variables that Should Probably not be Removed 43 2.20 Removal of Duplicate Records 44 2.21 A Word About ID Fields 45 CHAPTER 3 EXPLORATORY DATA ANALYSIS 54 3.1 Hypothesis Testing Versus Exploratory Data Analysis 54 3.2 Getting to Know the Data Set 54 3.3 Exploring Categorical Variables 56 3.4 Exploring Numeric Variables 64 3.5 Exploring Multivariate Relationships 69 3.6 Selecting Interesting Subsets of the Data for Further Investigation 70 3.7 Using EDA to Uncover Anomalous Fields 71 3.8 Binning Based on Predictive Value 72 3.9 Deriving New Variables: Flag Variables 75 3.10 Deriving New Variables: Numerical Variables 77 3.11 Using EDA to Investigate Correlated Predictor Variables 78 3.12 Summary of Our EDA 81 CHAPTER 4 DIMENSION-REDUCTION METHODS 92 4.1 Need for Dimension-Reduction in Data Mining 92 4.2 Principal Components Analysis 93 4.3 Applying PCA to the Houses Data Set 96 4.4 How Many Components Should We Extract? 102 4.5 Profiling the Principal Components 105 4.6 Communalities 108 4.7 Validation of the Principal Components 110 4.8 Factor Analysis 110 4.9 Applying Factor Analysis to the Adult Data Set 111 4.10 Factor Rotation 114 4.11 User-Defined Composites 117 4.12 An Example of a User-Defined Composite 118 PART II STATISTICAL ANALYSIS 129 CHAPTER 5 UNIVARIATE STATISTICAL ANALYSIS 131 5.1 Data Mining Tasks in Discovering Knowledge in Data 131 5.2 Statistical Approaches to Estimation and Prediction 131 5.3 Statistical Inference 132 5.4 How Confident are We in Our Estimates? 133 5.5 Confidence Interval Estimation of the Mean 134 5.6 How to Reduce the Margin of Error 136 5.7 Confidence Interval Estimation of the Proportion 137 5.8 Hypothesis Testing for the Mean 138 5.9 Assessing the Strength of Evidence Against the Null Hypothesis 140 5.10 Using Confidence Intervals to Perform Hypothesis Tests 141 5.11 Hypothesis Testing for the Proportion 143 CHAPTER 6 MULTIVARIATE STATISTICS 148 6.1 Two-Sample t-Test for Difference in Means 148 6.2 Two-Sample Z-Test for Difference in Proportions 149 6.3 Test for the Homogeneity of Proportions 150 6.4 Chi-Square Test for Goodness of Fit of Multinomial Data 152 6.5 Analysis of Variance 153 CHAPTER 7 PREPARING TO MODEL THE DATA 160 7.1 Supervised Versus Unsupervised Methods 160 7.2 Statistical Methodology and Data Mining Methodology 161 7.3 Cross-Validation 161 7.4 Overfitting 163 7.5 Bias–Variance Trade-Off 164 7.6 Balancing the Training Data Set 166 7.7 Establishing Baseline Performance 167 CHAPTER 8 SIMPLE LINEAR REGRESSION 171 8.1 An Example of Simple Linear Regression 171 8.2 Dangers of Extrapolation 177 8.3 How Useful is the Regression? The Coefficient of Determination, r2 178 8.4 Standard Error of the Estimate, s 183 8.5 Correlation Coefficient r 184 8.6 Anova Table for Simple Linear Regression 186 8.7 Outliers, High Leverage Points, and Influential Observations 186 8.8 Population Regression Equation 195 8.9 Verifying the Regression Assumptions 198 8.10 Inference in Regression 203 8.11 t-Test for the Relationship Between x and y 204 8.12 Confidence Interval for the Slope of the Regression Line 206 8.13 Confidence Interval for the Correlation Coefficient p 208 8.14 Confidence Interval for the Mean Value of y Given x 210 8.15 Prediction Interval for a Randomly Chosen Value of y Given x 211 8.16 Transformations to Achieve Linearity 213 8.17 Box–Cox Transformations 220 CHAPTER 9 MULTIPLE REGRESSION AND MODEL BUILDING 236 9.1 An Example of Multiple Regression 236 9.2 The Population Multiple Regression Equation 242 9.3 Inference in Multiple Regression 243 9.4 Regression with Categorical Predictors, Using Indicator Variables 249 9.5 Adjusting R2: Penalizing Models for Including Predictors that are not Useful 256 9.6 Sequential Sums of Squares 257 9.7 Multicollinearity 258 9.8 Variable Selection Methods 266 9.9 Gas Mileage Data Set 270 9.10 An Application of Variable Selection Methods 271 9.11 Using the Principal Components as Predictors in Multiple Regression 279 PART III CLASSIFICATION 299 CHAPTER 10 k-NEAREST NEIGHBOR ALGORITHM 301 10.1 Classification Task 301 10.2 k-Nearest Neighbor Algorithm 302 10.3 Distance Function 305 10.4 Combination Function 307 10.5 Quantifying Attribute Relevance: Stretching the Axes 309 10.6 Database Considerations 310 10.7 k-Nearest Neighbor Algorithm for Estimation and Prediction 310 10.8 Choosing k 311 10.9 Application of k-Nearest Neighbor Algorithm Using IBM/SPSS Modeler 312 CHAPTER 11 DECISION TREES 317 11.1 What is a Decision Tree? 317 11.2 Requirements for Using Decision Trees 319 11.3 Classification and Regression Trees 319 11.4 C4.5 Algorithm 326 11.5 Decision Rules 332 11.6 Comparison of the C5.0 and CART Algorithms Applied to Real Data 332 CHAPTER 12 NEURAL NETWORKS 339 12.1 Input and Output Encoding 339 12.2 Neural Networks for Estimation and Prediction 342 12.3 Simple Example of a Neural Network 342 12.4 Sigmoid Activation Function 344 12.5 Back-Propagation 345 12.6 Gradient-Descent Method 346 12.7 Back-Propagation Rules 347 12.8 Example of Back-Propagation 347 12.9 Termination Criteria 349 12.10 Learning Rate 350 12.11 Momentum Term 351 12.12 Sensitivity Analysis 353 12.13 Application of Neural Network Modeling 353 CHAPTER 13 LOGISTIC REGRESSION 359 13.1 Simple Example of Logistic Regression 359 13.2 Maximum Likelihood Estimation 361 13.3 Interpreting Logistic Regression Output 362 13.4 Inference: are the Predictors Significant? 363 13.5 Odds Ratio and Relative Risk 365 13.6 Interpreting Logistic Regression for a Dichotomous Predictor 367 13.7 Interpreting Logistic Regression for a Polychotomous Predictor 370 13.8 Interpreting Logistic Regression for a Continuous Predictor 374 13.9 Assumption of Linearity 378 13.10 Zero-Cell Problem 382 13.11 Multiple Logistic Regression 384 13.12 Introducing Higher Order Terms to Handle Nonlinearity 388 13.13 Validating the Logistic Regression Model 395 13.14 WEKA: Hands-On Analysis Using Logistic Regression 399 CHAPTER 14 NAÏVE BAYES AND BAYESIAN NETWORKS 414 14.1 Bayesian Approach 414 14.2 Maximum a Posteriori (Map) Classification 416 14.3 Posterior Odds Ratio 420 14.4 Balancing the Data 422 14.5 Naïve Bayes Classification 423 14.6 Interpreting the Log Posterior Odds Ratio 426 14.7 Zero-Cell Problem 428 14.8 Numeric Predictors for Naïve Bayes Classification 429 14.9 WEKA: Hands-on Analysis Using Naïve Bayes 432 14.10 Bayesian Belief Networks 436 14.11 Clothing Purchase Example 436 14.12 Using the Bayesian Network to Find Probabilities 439 CHAPTER 15 MODEL EVALUATION TECHNIQUES 451 15.1 Model Evaluation Techniques for the Description Task 451 15.2 Model Evaluation Techniques for the Estimation and Prediction Tasks 452 15.3 Model Evaluation Measures for the Classification Task 454 15.4 Accuracy and Overall Error Rate 456 15.5 Sensitivity and Specificity 457 15.6 False-Positive Rate and False-Negative Rate 458 15.7 Proportions of True Positives, True Negatives, False Positives, and False Negatives 458 15.8 Misclassification Cost Adjustment to Reflect Real-World Concerns 460 15.9 Decision Cost/Benefit Analysis 462 15.10 Lift Charts and Gains Charts 463 15.11 Interweaving Model Evaluation with Model Building 466 15.12 Confluence of Results: Applying a Suite of Models 466 CHAPTER 16 COST-BENEFIT ANALYSIS USING DATA-DRIVEN COSTS 471 16.1 Decision Invariance Under Row Adjustment 471 16.2 Positive Classification Criterion 473 16.3 Demonstration of the Positive Classification Criterion 474 16.4 Constructing the Cost Matrix 474 16.5 Decision Invariance Under Scaling 476 16.6 Direct Costs and Opportunity Costs 478 16.7 Case Study: Cost-Benefit Analysis Using Data-Driven Misclassification Costs 478 16.8 Rebalancing as a Surrogate for Misclassification Costs 483 CHAPTER 17 COST-BENEFIT ANALYSIS FOR TRINARY AND k-NARY CLASSIFICATION MODELS 491 17.1 Classification Evaluation Measures for a Generic Trinary Target 491 17.2 Application of Evaluation Measures for Trinary Classification to the Loan Approval Problem 494 17.3 Data-Driven Cost-Benefit Analysis for Trinary Loan Classification Problem 498 17.4 Comparing Cart Models with and without Data-Driven Misclassification Costs 500 17.5 Classification Evaluation Measures for a Generic k-Nary Target 503 17.6 Example of Evaluation Measures and Data-Driven Misclassification Costs for k-Nary Classification 504 CHAPTER 18 GRAPHICAL EVALUATION OF CLASSIFICATION MODELS 510 18.1 Review of Lift Charts and Gains Charts 510 18.2 Lift Charts and Gains Charts Using Misclassification Costs 510 18.3 Response Charts 511 18.4 Profits Charts 512 18.5 Return on Investment (ROI) Charts 514 PART IV CLUSTERING 521 CHAPTER 19 HIERARCHICAL AND k-MEANS CLUSTERING 523 19.1 The Clustering Task 523 19.2 Hierarchical Clustering Methods 525 19.3 Single-Linkage Clustering 526 19.4 Complete-Linkage Clustering 527 19.5 k-Means Clustering 529 19.6 Example of k-Means Clustering at Work 530 19.7 Behavior of MSB, MSE, and Pseudo-F as the k-Means Algorithm Proceeds 533 19.8 Application of k-Means Clustering Using SAS Enterprise Miner 534 19.9 Using Cluster Membership to Predict Churn 537 CHAPTER 20 KOHONEN NETWORKS 542 20.1 Self-Organizing Maps 542 20.2 Kohonen Networks 544 20.3 Example of a Kohonen Network Study 545 20.4 Cluster Validity 549 20.5 Application of Clustering Using Kohonen Networks 549 20.6 Interpreting The Clusters 551 20.7 Using Cluster Membership as Input to Downstream Data Mining Models 556 CHAPTER 21 BIRCH CLUSTERING 560 21.1 Rationale for Birch Clustering 560 21.2 Cluster Features 561 21.3 Cluster Feature Tree 562 21.4 Phase 1: Building the CF Tree 562 21.5 Phase 2: Clustering the Sub-Clusters 564 21.6 Example of Birch Clustering, Phase 1: Building the CF Tree 565 21.7 Example of Birch Clustering, Phase 2: Clustering the Sub-Clusters 570 21.8 Evaluating the Candidate Cluster Solutions 571 21.9 Case Study: Applying Birch Clustering to the Bank Loans Data Set 571 CHAPTER 22 MEASURING CLUSTER GOODNESS 582 22.1 Rationale for Measuring Cluster Goodness 582 22.2 The Silhouette Method 583 22.3 Silhouette Example 584 22.4 Silhouette Analysis of the IRIS Data Set 585 22.5 The Pseudo-F Statistic 590 22.6 Example of the Pseudo-F Statistic 591 22.7 Pseudo-F Statistic Applied to the IRIS Data Set 592 22.8 Cluster Validation 593 22.9 Cluster Validation Applied to the Loans Data Set 594 PART V ASSOCIATION RULES 601 CHAPTER 23 ASSOCIATION RULES 603 23.1 Affinity Analysis and Market Basket Analysis 603 23.2 Support, Confidence, Frequent Itemsets, and the a Priori Property 605 23.3 How Does the A Priori Algorithm Work (Part 1)? Generating Frequent Itemsets 607 23.4 How Does the A Priori Algorithm Work (Part 2)? Generating Association Rules 608 23.5 Extension from Flag Data to General Categorical Data 611 23.6 Information-Theoretic Approach: Generalized Rule Induction Method 612 23.7 Association Rules are Easy to do Badly 614 23.8 How can we Measure the Usefulness of Association Rules? 615 23.9 Do Association Rules Represent Supervised or Unsupervised Learning? 616 23.10 Local Patterns Versus Global Models 617 PART VI ENHANCING MODEL PERFORMANCE 623 CHAPTER 24 SEGMENTATION MODELS 625 24.1 The Segmentation Modeling Process 625 24.2 Segmentation Modeling Using EDA to Identify the Segments 627 24.3 Segmentation Modeling using Clustering to Identify the Segments 629 CHAPTER 25 ENSEMBLE METHODS: BAGGING AND BOOSTING 637 25.1 Rationale for Using an Ensemble of Classification Models 637 25.2 Bias, Variance, and Noise 639 25.3 When to Apply, and not to apply, Bagging 640 25.4 Bagging 641 25.5 Boosting 643 25.6 Application of Bagging and Boosting Using IBM/SPSS Modeler 647 CHAPTER 26 MODEL VOTING AND PROPENSITY AVERAGING 653 26.1 Simple Model Voting 653 26.2 Alternative Voting Methods 654 26.3 Model Voting Process 655 26.4 An Application of Model Voting 656 26.5 What is Propensity Averaging? 660 26.6 Propensity Averaging Process 661 26.7 An Application of Propensity Averaging 661 PART VII FURTHER TOPICS 669 CHAPTER 27 GENETIC ALGORITHMS 671 27.1 Introduction To Genetic Algorithms 671 27.2 Basic Framework of a Genetic Algorithm 672 27.3 Simple Example of a Genetic Algorithm at Work 673 27.4 Modifications and Enhancements: Selection 676 27.5 Modifications and Enhancements: Crossover 678 27.6 Genetic Algorithms for Real-Valued Variables 679 27.7 Using Genetic Algorithms to Train a Neural Network 681 27.8 WEKA: Hands-On Analysis Using Genetic Algorithms 684 CHAPTER 28 IMPUTATION OF MISSING DATA 695 28.1 Need for Imputation of Missing Data 695 28.2 Imputation of Missing Data: Continuous Variables 696 28.3 Standard Error of the Imputation 699 28.4 Imputation of Missing Data: Categorical Variables 700 28.5 Handling Patterns in Missingness 701 PART VIII CASE STUDY: PREDICTING RESPONSE TO DIRECT-MAIL MARKETING 705 CHAPTER 29 CASE STUDY, PART 1: BUSINESS UNDERSTANDING, DATA PREPARATION, AND EDA 707 29.1 Cross-Industry Standard Practice for Data Mining 707 29.2 Business Understanding Phase 709 29.3 Data Understanding Phase, Part 1: Getting a Feel for the Data Set 710 29.4 Data Preparation Phase 714 29.5 Data Understanding Phase, Part 2: Exploratory Data Analysis 721 CHAPTER 30 CASE STUDY, PART 2: CLUSTERING AND PRINCIPAL COMPONENTS ANALYSIS 732 30.1 Partitioning the Data 732 30.2 Developing the Principal Components 733 30.3 Validating the Principal Components 737 30.4 Profiling the Principal Components 737 30.5 Choosing the Optimal Number of Clusters Using Birch Clustering 742 30.6 Choosing the Optimal Number of Clusters Using k-Means Clustering 744 30.7 Application of k-Means Clustering 745 30.8 Validating the Clusters 745 30.9 Profiling the Clusters 745 CHAPTER 31 CASE STUDY, PART 3: MODELING AND EVALUATION FOR PERFORMANCE AND INTERPRETABILITY 749 31.1 Do you Prefer the Best Model Performance, or a Combination of Performance and Interpretability? 749 31.2 Modeling and Evaluation Overview 750 31.3 Cost-Benefit Analysis Using Data-Driven Costs 751 31.4 Variables to be Input to the Models 753 31.5 Establishing the Baseline Model Performance 754 31.6 Models that use Misclassification Costs 755 31.7 Models that Need Rebalancing as a Surrogate for Misclassification Costs 756 31.8 Combining Models Using Voting and Propensity Averaging 757 31.9 Interpreting the Most Profitable Model 758 CHAPTER 32 CASE STUDY, PART 4: MODELING AND EVALUATION FOR HIGH PERFORMANCE ONLY 762 32.1 Variables to be Input to the Models 762 32.2 Models that use Misclassification Costs 762 32.3 Models that Need Rebalancing as a Surrogate for Misclassification Costs 764 32.4 Combining Models using Voting and Propensity Averaging 765 32.5 Lessons Learned 766 32.6 Conclusions 766 APPENDIX A DATA SUMMARIZATION AND VISUALIZATION 768 Part 1: Summarization 1: Building Blocks of Data Analysis 768 Part 2: Visualization: Graphs and Tables for Summarizing and Organizing Data 770 Part 3: Summarization 2: Measures of Center, Variability, and Position 774 Part 4: Summarization and Visualization of Bivariate Relationships 777 INDEX 781

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Book SynopsisComputer security touches every part of our daily lives from our computers and connected devices to the wireless signals around us. Breaches have real and immediate financial, privacy, and safety consequences. This handbook has compiled advice from top professionals working in the real world about how to minimize the possibility of computer security breaches in your systems. Written for professionals and college students, it provides comprehensive best guidance about how to minimize hacking, fraud, human error, the effects of natural disasters, and more. This essential and highly-regarded reference maintains timeless lessons and is fully revised and updated with current information on security issues for social networks, cloud computing, virtualization, and more.Table of ContentsPreface Acknowledgments About the Editors About the Contributors A Note to Instructors PART I FOUNDATIONS OF COMPUTER SECURITY Chapter 1 Brief History and Mission of Information System Security (Seymour Bosworth and Robert V. Jacobson) Chapter 2 History of Computer Crime Chapter 3 Toward a New Framework for Information Security (Donn B. Parker, CISSP) Chapter 4 Hardware Elements of Security (Sy Bosworth and Stephen Cobb) Chapter 5 Data Communications and Information Security (Raymond Panko and Eric Fisher) Chapter 6 Local Area Network Topologies, Protocols, and Design (Gary C. Kessler) Chapter 7 Encryption (Stephen Cobb and Corinne LeFrançois) Chapter 8 Using a Common Language for Computer Security Incident Information (John D. Howard) Chapter 9 Mathematical Models of Computer Security (Matt Bishop) Chapter 10 Understanding Studies and Surveys of Computer Crime (M. E. Kabay) Chapter 11 Fundamentals of Intellectual Property Law (William A. Zucker and Scott J. Nathan) PART II THREATS AND VULNERABILITIES Chapter 12 The Psychology of Computer Criminals (Q. Campbell and David M. Kennedy) Chapter 13 The Insider Threat (Gary L. Tagg, CISSP) Chapter 14 Information Warfare (Seymour Bosworth) Chapter 15 Penetrating Computer Systems and Networks (Chey Cobb, Stephen Cobb, M. E. Kabay, and Tim Crothers) Chapter 16 Malicious Code (Robert Guess and Eric Salveggio) Chapter 17 Mobile Code (Robert Gezelter) Chapter 18 Denial-of-Service Attacks (Gary C. Kessler) Chapter 19 Social-engineering and low-tech attacks (Karthik Raman, Susan Baumes, Kevin Beets, and Carl Ness) Chapter 20 Spam, Phishing, and Trojans: Attacks Meant To Fool (Stephen Cobb) Chapter 21 Web-Based Vulnerabilities (Anup K. Ghosh, Kurt Baumgarten, Jennifer Hadley, and Steven Lovaas) Chapter 22 Physical Threats to the Information Infrastructure (Franklin Platt) PART III PREVENTION: TECHNICAL DEFENSES Chapter 23 Protecting the Physical Information Infrastructure (Franklin Platt) Chapter 24 Operating System Security (William Stallings) Chapter 25 Local Area Networks (N. Todd Pritsky, Joseph R. Bumblis, and Gary C. Kessler) Chapter 26 Gateway Security Devices (Justin Opatrny) Chapter 27 Intrusion Detection and Intrusion Prevention Devices (Rebecca Gurley Bace) Chapter 28: Identification and Authentication (Ravi Sandhu, Jennifer Hadley, Steven Lovaas, and Nicholas Takacs) Chapter 29: Biometric Authentication (Eric Salveggio, Steven Lovaas, David R. Lease, and Robert Guess) Chapter 30: E-Commerce and Web Server Safeguards (Robert Gezelter) Chapter 31: Web Monitoring and Content Filtering (Steven Lovaas) Chapter 32 Virtual Private Networks and Secure Remote Access (Justin Opatrny and Carl Ness Chapter 33 802.11 Wireless LAN Security (Gary L. Tagg, CISSP and Jason Sinchak, CISSP) Chapter 34 Securing VoIP (Christopher Dantos and John Mason) Chapter 35 Securing P2P, IM, SMS, and Collaboration Tools (Carl Ness) Chapter 36 Securing Stored Data (David J. Johnson, Nicholas Takacs, Jennifer Hadley, and M. E. Kabay) Chapter 37: PKI and Certificate Authorities (Santosh Chokhani, Padgett Peterson, and Steven Lovaas) Chapter 38: Writing Secure Code (Lester E. Nichols, M. E. Kabay, and Timothy Braithwaite) Chapter 39 Software Development and Quality Assurance (Diane E. Levine, John Mason, and Jennifer Hadley) Chapter 40: Managing Software Patches and Vulnerabilities (Karen Scarfone, Peter Mell, and Murugiah Souppaya) Chapter 41: Antivirus Technology (Chey Cobb and Allysa Myers) Chapter 42: Protecting Digital Rights: Technical Approaches (Robert Guess, Jennifer Hadley, Steven Lovaas, and Diane E. Levine) PART IV PREVENTION: HUMAN FACTORS Chapter 43 Ethical Decision Making and High Technology (James Landon Linderman) Chapter 44: Security Policy Guidelines (M. E. Kabay and Bridgitt Robertson) Chapter 45: Employment Practices and Policies (M. E. Kabay and Bridgitt Robertson) Chapter 46 Vulnerability Assessment (Rebecca Gurley Bace and Jason Sinchak) Chapter 47: Operations Security and Production Controls (M. E. Kabay, Don Holden, and Myles Walsh) Chapter 48: E-Mail and Internet Use Policies (M. E. Kabay and Nicholas Takacs) Chapter 49: Implementing a Security-Awareness Program (K. Rudolph) Chapter 50 Using Social Psychology to Implement Security Policies (M. E. Kabay, Bridgitt Robertson, Mani Akella, and D. T. Lang) Chapter 51: Security Standards for Products (Paul Brusil and Noel Zakin) PART V DETECTING SECURITY BREACHES Chapter 52: Application Controls (Myles Walsh & Susan Baumes) Chapter 53: Monitoring and Control Systems (Caleb S. Coggins and Diane E. Levine) Chapter 54: Security Audits (Donald Glass, Richard O. Moore III, Chris Davis, John Mason, David Gursky, James Thomas, Wendy Carr, M. E. Kabay and Diane Levine) Chapter 55: Cyber Investigation1 (Peter Stephenson) PART VI RESPONSE AND REMEDIATION Chapter 56: Computer Security Incident Response Teams1 (Michael Miora, M. E. Kabay, and Bernie Cowens) Chapter 57: Data Backups and Archives (M. E. Kabay and Don Holden) Chapter 58: Business Continuity Planning (Michael Miora) Chapter 59: Disaster Recovery (Michael Miora) Chapter 60: Insurance Relief (Robert A. Parisi, Jr., John F. Mullen and Kevin Apollo) Chapter 61 Working with Law Enforcement (David A. Land) PART VII MANAGEMENT’S ROLE IN SECURITY Chapter 62 Quantitative Risk Assessment and Risk Management (Robert V. Jacobson & Susan Baumes) Chapter 63: Management Responsibilities and Liabilities (Carl Hallberg, M. E. Kabay, Bridgitt Robertson, and Arthur E. Hutt) Chapter 64: US Legal and Regulatory Security Issues (Timothy Virtue) Chapter 65: The Role of the CISO (Karen F. Worstell) Chapter 66: Developing Security Policies (M. E. Kabay and Sean Kelley) Chapter 67 Developing Classification Policies For Data (Karthik Raman, Kevin Beets, And M. E. Kabay) Chapter 68: Outsourcing and Security (Kip Boyle, Michael Buglewicz, and Steven Lovaas) PART VIII PUBLIC POLICY AND OTHER CONSIDERATIONS Chapter 69: Privacy in Cyberspace: US and European Perspectives (Henry L. Judy, Scott L. David, Benjamin S. Hayes, Jeffrey B. Ritter, Marc Rotenberg and M. E. Kabay) Chapter 70: Anonymity and Identity in Cyberspace (M. E. Kabay, Eric Salveggio, Robert Guess, and Russell D. Rosco) Chapter 71: Healthcare Security and Privacy (Paul Brusil) Chapter 72: Legal and Policy Issues of Censorship and Content Filtering (Lee Tien, Seth Finkelstein, and Steven Lovaas) Chapter 73: Expert Witnesses and the Daubert Challenge (Chey Cobb) Chapter 74: Professional Certification and Training in Information Assurance (M. E. Kabay, Christopher Christian, Kevin Henry and Sondra Schneider) Chapter 75 Undergraduate and Graduate Education in Information Assurance (Vic Maconachy and Seymour Bosworth) Chapter 76: The Future of Information Assurance (Jeremy A. Hansen) Index

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Book SynopsisReviews the latest advances in the all-important field of scalable computing In telecommunications and software engineering, scalability is the ability of a system, network, or process to either handle growing amounts of work in a graceful manner or be enlarged to accommodate that growth. It is a desirable property for many scientific, industrial, and business applications and an important feature for hardware. This immersive book summarizes the latest research achievements in the field of scalable computing and covers new topics that have emerged recently on computing and communications, such as unconventional computing, green and sustainable computing, cloud and volunteer computing, and more. Filled with contributions from world-renowned engineers, researchers, and IT professionals in diverse areas, Scalable Computing and Communications covers: Circuit and component design Operating systems Green computing NetworkTable of ContentsPreface xix Contributors xxi 1. Scalable Computing and Communications: Past, Present, and Future 1Yanhui Wu, Kashif Bilal, Samee U. Khan, Lizhe Wang, and Albert Y. Zomaya 1.1 Scalable Computing and Communications 1 References 4 2. Reliable Minimum Connected Dominating Sets for Topology Control in Probabilistic Wireless Sensor Networks 7Jing (Selena) He, Shouling Ji, Yi Pan, and Yingshu Li 2.1 Topology Control in Wireless Sensor Networks (WSNs) 7 2.2 DS-Based Topology Control 10 2.3 Deterministic WSNs and Probabilistic WSNs 12 2.4 Reliable MCDS Problem 13 2.5 A GA to Construct RMCDS-GA 17 2.6 Performance Evaluation 26 2.7 Conclusions 27 References 28 3. Peer Selection Schemes in Scalable P2P Video Streaming Systems 31Xin Jin and Yu-Kwong Kwok 3.1 Introduction 31 3.2 Overlay Structures 32 3.3 Peer Selection for Overlay Construction 34 3.4 A Game Theoretic Perspective on Peer Selection 45 3.5 Discussion and Future Work 47 3.6 Summary 48 References 49 4. Multicore and Many-Core Computing 55Ioannis E. Venetis 4.1 Introduction 55 4.2 Architectural Options for Multicore Systems 60 4.3 Multicore Architecture Examples 64 4.4 Programming Multicore Architectures 67 4.5 Many-Core Architectures 74 4.6 Many-Core Architecture Examples 75 4.7 Summary 77 References 77 5. Scalable Computing on Large Heterogeneous CPU/GPU Supercomputers 81Fengshun Lu, Kaijun Ren, Junqiang Song, and Jinjun Chen 5.1 Introduction 81 5.2 Heterogeneous Computing Environments 82 5.3 Scalable Programming Patterns for Large GPU Clusters 84 5.4 Hybrid Implementations 87 5.5 Experimental Results 89 5.6 Conclusions 94 Acknowledgments 94 References 94 6. Diagnosability of Multiprocessor Systems 97Chia-Wei Lee and Sun-Yuan Hsieh 6.1 Introduction 97 6.2 Fundamental Concepts 98 6.3 Diagnosability of (1,2)-MCNS under PMC Model 103 6.4 Diagnosability of 2-MCNS under MM* Model 105 6.5 Application to Multiprocessor Systems 110 6.6 Concluding Remarks 122 References 122 7. A Performance Analysis Methodology for MultiCore, Multithreaded Processors 125Miao Ju, Hun Jung, and Hao Che 7.1 Introduction 125 7.2 Methodology 126 7.3 Simulation Tool (ST) 130 7.4 Analytic Modeling Technique 132 7.5 Testing 136 7.6 Related Work 139 7.7 Conclusions and Future Work 141 References 141 8. The Future in Mobile Multicore Computing 145Blake Hurd, Chiu C. Tan, and Jie Wu 8.1 Introduction 145 8.2 Background 146 8.3 Hardware Initiatives 148 8.4 Software Initiatives 151 8.5 Additional Discussion 152 8.6 Future Trends 153 8.7 Conclusion 154 References 155 9. Modeling and Algorithms for Scalable and Energy-Efficient Execution on Multicore Systems 157Dong Li, Dimitrios S. Nikolopoulos, and Kirk W. Cameron 9.1 Introduction 157 9.2 Model-Based Hybrid Message-Passing Interface (MPI)/OpenMP Power-Aware Computing 158 9.3 Power-Aware MPI Task Aggregation Prediction 170 9.4 Conclusions 181 References 182 10. Cost Optimization for Scalable Communication in Wireless Networks with Movement-Based Location Management 185Keqin Li 10.1 Introduction 185 10.2 Background Information 187 10.3 Cost Measure and Optimization for a Single User 190 10.4 Cost Optimization with Location Update Constraint 192 10.5 Cost Optimization with Terminal Paging Constraint 196 10.6 Numerical Data 201 10.7 Concluding Remarks 206 References / 206 11. A Framework for Semiautomatic Explicit Parallelization 209Ritu Arora, Purushotham Bangalore, and Marjan Mernik 11.1 Introduction 209 11.2 Explicit Parallelization Using MPI 210 11.3 Building Blocks of FraSPA 211 11.4 Evaluation of FraSPA through Case Studies 215 11.5 Lessons Learned 221 11.6 Related Work 222 11.7 Summary 224 References 224 12. Fault Tolerance and Transmission Reliability in Wireless Networks 227Wolfgang W. Bein and Doina Bein 12.1 Introduction: Reliability Issues in Wireless and Sensor Networks 227 12.2 Reliability and Fault Tolerance of Coverage Models for Sensor Networks 230 12.3 Fault-Tolerant k-Fold Pivot Routing in Wireless Sensor Networks 238 12.4 Impact of Variable Transmission Range in All-Wireless Networks 244 12.5 Conclusions and Open Problems 250 References / 251 13. Optimizing and Tuning Scientifi c Codes 255Qing Yi 13.1 Introduction 255 13.2 An Abstract View of the Machine Architecture 256 13.3 Optimizing Scientifi c Codes 256 13.4 Empirical Tuning of Optimizations 262 13.5 Related Work 272 13.6 Summary and Future Work 273 Acknowledgments 273 References 273 14. Privacy and Confi dentiality in Cloud Computing 277Khaled M. Khan and Qutaibah Malluhi 14.1 Introduction 277 14.2 Cloud Stakeholders and Computational Assets 278 14.3 Data Privacy and Trust 280 14.4 A Cloud Computing Example 281 14.5 Conclusion 288 Acknowledgments 288 References 288 15. Reputation Management Systems for Peer-to-Peer Networks 291Fang Qi, Haiying Shen, Harrison Chandler, Guoxin Liu, and Ze Li 15.1 Introduction 291 15.2 Reputation Management Systems 292 15.3 Case Study of Reputation Systems 307 15.4 Open Problems 316 15.5 Conclusion 316 Acknowledgments 317 References 317 16. Toward a Secure Fragment Allocation of Files in Heterogeneous Distributed Systems 321Yun Tian, Mohammed I. Alghamdi, Xiaojun Ruan, Jiong Xie, and Xiao Qin 16.1 Introduction 321 16.2 Related Work 323 16.3 System and Threat Models 325 16.4 S-FAS: A Secure Fragment Allocation Scheme 327 16.5 Assurance Models 329 16.6 Sap Allocation Principles and Prototype 332 16.7 Evaluation of System Assurance and Performance 333 16.8 Conclusion 339 Acknowledgments 341 References 341 17. Adopting Compression in Wireless Sensor Networks 343Xi Deng and Yuanyuan Yang 17.1 Introduction 343 17.2 Compression in Sensor Nodes 345 17.3 Compression Effect on Packet Delay 348 17.4 Online Adaptive Compression Algorithm 350 17.5 Performance Evaluations 360 17.6 Summary 362 References 363 18. GFOG: Green and Flexible Opportunistic Grids 365Harold Castro, Mario Villamizar, German Sotelo, Cesar O. Diaz, Johnatan Pecero, Pascal Bouvry, and Samee U. Khan 18.1 Introduction 365 18.2 Related Work 366 18.3 UnaGrid Infrastructure 369 18.4 Energy Consumption Model 372 18.5 Experimental Results 374 18.6 Conclusions and Future Work 382 References 382 19. Maximizing Real-Time System Utilization by Adjusting Task Computation Times 387Nasro Min-Allah, Samee Ullah Khan, Yongji Wang, Joanna Kolodziej, and Nasir Ghani 19.1 Introduction 387 19.2 Expressing Task Schedulability in Polylinear Surfaces 389 19.3 Task Execution Time Adjustment Based on the P-Bound 391 19.4 Conclusions 393 Acknowledgments 393 References 393 20. Multilevel Exploration of the Optimization Landscape through Dynamical Fitness for Grid Scheduling 395Joanna Kolodziej 20.1 Introduction 395 20.2 Statement of the Problem 397 20.3 General Characteristics of the Optimization Landscape 399 20.4 Multilevel Metaheuristic Schedulers 402 20.5 Empirical Analysis 408 20.6 Conclusions 417 References 417 21. Implementing Pointer Jumping for Exact Inference on Many-Core Systems 419Yinglong Xia, Nam Ma, and Viktor K. Prasanna 21.1 Introduction 419 21.2 Background 420 21.3 Related Work 422 21.4 Pointer Jumping-Based Algorithms for Scheduling Exact Inference 423 21.5 Analysis with Respect to Many-Core Processors 424 21.6 From Exact Inference to Generic Directed Acyclic Graph (DAG)-Structured Computations 427 21.7 Experiments 428 21.8 Conclusions 434 References 435 22. Performance Optimization of Scientifi c Applications Using an Autonomic Computing Approach 437Ioana Banicescu, Florina M. Ciorba, and Srishti Srivastava 22.1 Introduction 437 22.2 Scientifi c Applications and Their Performance 439 22.3 Load Balancing via DLS 441 22.4 The Use of Machine Learning in Improving the Performance of Scientifi c Applications 441 22.5 Design Strategies and an Integrated Framework 445 22.6 Experimental Results, Analysis, and Evaluation 455 22.7 Conclusions, Future Work, and Open Problems 462 Acknowledgments 463 References 463 23. A Survey of Techniques for Improving Search Engine Scalability through Profi ling, Prediction, and Prefetching of Query Results 467C. Shaun Wagner, Sahra Sedigh, Ali R. Hurson, and Behrooz Shirazi 23.1 Introduction 467 23.2 Modeling User Behavior 472 23.3 Grouping Users into Neighborhoods of Similarity 474 23.4 Similarity Metrics 481 23.5 Conclusion and Future Work 497 Appendix A Comparative Analysis of Comparison Algorithms 498 Appendix B Most Popular Searches 501 References 502 24. KNN Queries in Mobile Sensor Networks 507Wei-Guang Teng and Kun-Ta Chuang 24.1 Introduction 507 24.2 Preliminaries and Infrastructure-Based KNN Queries 509 24.3 Infrastructure-Free KNN Queries 511 24.4 Future Research Directions 519 24.5 Conclusions 519 References 520 25. Data Partitioning for Designing and Simulating Efficient Huge Databases 523Ladjel Bellatreche, Kamel Boukhalfa, Pascal Richard, and Soumia Benkrid 25.1 Introduction 523 25.2 Background and Related Work 527 25.3 Fragmentation Methodology 532 25.4 Hardness Study 535 25.5 Proposed Selection Algorithms 538 25.6 Impact of HP on Data Warehouse Physical Design 544 25.7 Experimental Studies 549 25.8 Physical Design Simulator Tool 553 25.9 Conclusion and Perspectives 559 References 560 26. Scalable Runtime Environments for Large-Scale Parallel Applications 563Camille Coti and Franck Cappello 26.1 Introduction 563 26.2 Goals of a Runtime Environment 565 26.3 Communication Infrastructure 567 26.4 Application Deployment 571 26.5 Fault Tolerance and Robustness 577 26.6 Case Studies 582 26.7 Conclusion 586 References 587 27. Increasing Performance through Optimization on APU 591Matthew Doerksen, Parimala Thulasiraman, and Ruppa Thulasiram 27.1 Introduction 591 27.2 Heterogeneous Architectures 591 27.3 Related Work 597 27.4 OpenCL, CUDA of the Future 600 27.5 Simple Introduction to OpenCL Programming 604 27.6 Performance and Optimization Summary 607 27.7 Application 607 27.8 Summary 609 Appendix 609 References 612 28. Toward Optimizing Cloud Computing: An Example of Optimization under Uncertainty 613Vladik Kreinovich 28.1 Cloud Computing: Why We Need It and How We Can Make It Most Efficient 613 28.2 Optimal Server Placement Problem: First Approximation 614 28.3 Server Placement in Cloud Computing: Toward a More Realistic Model 618 28.4 Predicting Cloud Growth: Formulation of the Problem and Our Approach to Solving This Problem 620 28.5 Predicting Cloud Growth: First Approximation 621 28.6 Predicting Cloud Growth: Second Approximation 622 28.7 Predicting Cloud Growth: Third Approximation 623 28.8 Conclusions and Future Work 625 Acknowledgments 625 Appendix: Description of Expenses Related to Cloud Computing 626 References 626 29. Modeling of Scalable Embedded Systems 629Arslan Munir, Sanjay Ranka, and Ann Gordon-Ross 29.1 Introduction 629 29.2 Embedded System Applications 631 29.3 Embedded Systems: Hardware and Software 634 29.4 Modeling: An Integral Part of the Embedded System Design Flow 638 29.5 Single- and Multiunit Embedded System Modeling 644 29.6 Conclusions 654 Acknowledgments 655 References 655 30. Scalable Service Composition in Pervasive Computing 659Joanna Siebert and Jiannong Cao 30.1 Introduction 659 30.2 Service Composition Framework 660 30.3 Approaches and Techniques for Scalable Service Composition in PvCE 664 30.4 Conclusions 671 References 671 31. Virtualization Techniques for Graphics Processing Units 675Pavan Balaji, Qian Zhu, and Wu-Chun Feng 31.1 Introduction 675 31.2 Background 677 31.3 VOCL Framework 677 31.4 VOCL Optimizations 682 31.5 Experimental Evaluation 687 31.6 Related Work 696 31.7 Concluding Remarks 696 References 697 32. Dense Linear Algebra on Distributed Heterogeneous Hardware with a Symbolic DAG Approach 699George Bosilca, Aurelien Bouteiller, Anthony Danalis, Thomas Herault, Piotr Luszczek, and Jack J. Dongara 32.1 Introduction and Motivation 699 32.2 Distributed Datafl ow by Symbolic Evaluation 701 32.3 The DAGuE Datafl ow Runtime 705 32.4 Datafl ow Representation 709 32.5 Programming Linear Algebra with DAGuE 716 32.6 Performance Evaluation 728 32.7 Conclusion 731 32.8 Summary 732 References 733 33. Fault-Tolerance Techniques for Scalable Computing 737Pavan Balaji, Darius Buntinas, and Dries Kimpe 33.1 Introduction and Trends in Large-Scale Computing Systems 737 33.2 Hardware Features for Resilience 738 33.3 Systems Software Features for Resilience 743 33.4 Application or Domain-Specifi c Fault-Tolerance Techniques 748 33.5 Summary 753 References 753 34. Parallel Programming Models for Scalable Computing 759James Dinan and Pavan Balaji 34.1 Introduction to Parallel Programming Models 759 34.2 The Message-Passing Interface (MPI) 761 34.3 Partitioned Global Address Space (PGAS) Models 765 34.4 Task-Parallel Programming Models 769 34.5 High-Productivity Parallel Programming Models 772 34.6 Summary and Concluding Remarks 775 Acknowledgment 775 References 775 35. Grid Simulation Tools for Job Scheduling and Data File Replication 777Javid Taheri, Albert Y. Zomaya, and Samee U. Khan 35.1 Introduction 777 35.2 Simulation Platforms 779 35.3 Problem Statement: Data-Aware Job Scheduling (DAJS) 792 References 795 Index 799

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Book SynopsisAn authoritative guide to investigating high-technology crimes Internet crime is seemingly ever on the rise, making the need for a comprehensive resource on how to investigate these crimes even more dire. This professional-level book--aimed at law enforcement personnel, prosecutors, and corporate investigators--provides you with the training you need in order to acquire the sophisticated skills and software solutions to stay one step ahead of computer criminals. Specifies the techniques needed to investigate, analyze, and document a criminal act on a Windows computer or network Places a special emphasis on how to thoroughly investigate criminal activity and now just perform the initial response Walks you through ways to present technically complicated material in simple terms that will hold up in court Features content fully updated for Windows Server 2008 R2 and Windows 7 Covers the emerging field of Windows Mobile forensics<Table of ContentsIntroduction xvii Part 1 Understanding and Exploiting Windows Networks 1 Chapter 1 Network Investigation Overview 3 Performing the Initial Vetting 3 Meeting with the Victim Organization 5 Understanding the Victim Network Information 6 Understanding the Incident 8 Identifying and Preserving Evidence 9 Establishing Expectations and Responsibilities 11 Collecting the Evidence 12 Analyzing the Evidence 15 Analyzing the Suspect’s Computers 18 Recognizing the Investigative Challenges of Microsoft Networks 21 The Bottom Line 22 Chapter 2 The Microsoft Network Structure 25 Connecting Computers 25 Windows Domains 27 Interconnecting Domains 29 Organizational Units 34 Users and Groups 35 Types of Accounts 36 Groups 40 Permissions 44 File Permissions 45 Share Permissions 48 Reconciling Share and File Permissions 50 Example Hack 52 The Bottom Line 61 Chapter 3 Beyond the Windows GUI 63 Understanding Programs, Processes, and Threads 64 Redirecting Process Flow 67 DLL Injection 70 Hooking 74 Maintaining Order Using Privilege Modes 78 Using Rootkits 80 The Bottom Line 83 Chapter 4: Windows Password Issues 85 Understanding Windows Password Storage 85 Cracking Windows Passwords Stored on Running Systems 88 Exploring Windows Authentication Mechanisms 98 LanMan Authentication 99 NTLM Authentication 103 Kerberos Authentication 108 Sniffing and Cracking Windows Authentication Exchanges 111 Using ScoopLM and BeatLM to Crack Passwords 114 Cracking Offline Passwords 121 Using Cain & Abel to Extract Windows Password Hashes 122 Accessing Passwords through the Windows Password Verifier 126 Extracting Password Hashes from RAM 127 Stealing Credentials from a Running System 128 The Bottom Line 134 Chapter 5 Windows Ports and Services 137 Understanding Ports 137 Using Ports as Evidence 142 Understanding Windows Services 149 The Bottom Line 155 Part 2 Analyzing the Computer 157 Chapter 6 Live-Analysis Techniques 159 Finding Evidence in Memory 159 Creating a Windows Live-Analysis Toolkit 161 Using DumpIt to Acquire RAM from a 64-Bit Windows 7 System 164 Using WinEn to Acquire RAM from a Windows 7 Environment 166 Using FTK Imager Lite to Acquire RAM from Windows Server 2008 167 Using Volatility 2.0 to Analyze a Windows 7 32-Bit RAM Image 169 Monitoring Communication with the Victim Box 173 Scanning the Victim System 176 The Bottom Line 178 Chapter 7 Windows Filesystems 179 Filesystems vs. Operating Systems 179 Understanding FAT Filesystems 183 Understanding NTFS Filesystems 198 Using NTFS Data Structures 198 Creating, Deleting, and Recovering Data in NTFS 205 Dealing with Alternate Data Streams 208 The exFAT Filesystem 212 The Bottom Line 213 Chapter 8 The Registry Structure 215 Understanding Registry Concepts 215 Registry History 217 Registry Organization and Terminology 217 Performing Registry Research 228 Viewing the Registry with Forensic Tools 232 Using EnCase to View the Registry 234 Examining Information Manually 234 Using EnScripts to Extract Information 236 Using AccessData’s Registry Viewer 246 Other Tools 251 The Bottom Line 254 Chapter 9 Registry Evidence 257 Finding Information in the Software Key 258 Installed Software 258 Last Logon 264 Banners 265 Exploring Windows Security, Action Center, and Firewall Settings 267 Analyzing Restore Point Registry Settings 276 Windows XP Restore Point Content 280 Analyzing Volume Shadow Copies for Registry Settings 284 Exploring Security Identifiers 290 Examining the Recycle Bin 291 Examining the ProfileList Registry Key 293 Investigating User Activity 295 Examining the PSSP and IntelliForms Keys 295 Examining the MRU Key 296 Examining the RecentDocs Key 298 Examining the TypedURLs Key 298 Examining the UserAssist Key 299 Extracting LSA Secrets 305 Using Cain & Abel to Extract LSA Secrets from Your Local Machine 306 Discovering IP Addresses 307 Dynamic IP Addresses 307 Getting More Information from the GUID-Named Interface 309 Compensating for Time Zone Offsets 312 Determining the Startup Locations 313 Exploring the User Profile Areas 316 Exploring Batch Files 318 Exploring Scheduled Tasks 318 Exploring the AppInit_DLL Key 320 Using EnCase and Registry Viewer 320 Using Autoruns to Determine Startups 320 The Bottom Line 322 Chapter 10 Introduction to Malware 325 Understanding the Purpose of Malware Analysis 325 Malware Analysis Tools and Techniques 329 Constructing an Effective Malware Analysis Toolkit 329 Analyzing Malicious Code 331 Monitoring Malicious Code 338 Monitoring Malware Network Traffic 346 The Bottom Line 348 Part 3 Analyzing the Logs 349 Chapter 11 Text-Based Logs 351 Parsing IIS Logs 351 Parsing FTP Logs 362 Parsing DHCP Server Logs 369 Parsing Windows Firewall Logs 373 Using Splunk 376 The Bottom Line 379 Chapter 12 Windows Event Logs 381 Understanding the Event Logs 381 Exploring Auditing Settings 384 Using Event Viewer 391 Opening and Saving Event Logs 403 Viewing Event Log Data 407 Searching with Event Viewer 411 The Bottom Line 418 Chapter 13 Logon and Account Logon Events 419 Begin at the Beginning 419 Comparing Logon and Account Logon Events 420 Analyzing Windows 2003/2008 Logon Events 422 Examining Windows 2003/2008 Account Logon Events 433 The Bottom Line 462 Chapter 14 Other Audit Events 463 The Exploitation of a Network 463 Examining System Log Entries 466 Examining Application Log Entries 473 Evaluating Account Management Events 473 Interpreting File and Other Object Access Events 490 Examining Audit Policy Change Events 500 The Bottom Line 503 Chapter 15 Forensic Analysis of Event Logs 505 Windows Event Log Files Internals 505 Windows Vista/7/2008 Event Logs 505 Windows XP/2003 Event Logs 513 Repairing Windows XP/2003 Corrupted Event Log Databases 524 Finding and Recovering Event Logs from Free Space 527 The Bottom Line 536 Part 4 Results, the Cloud, and Virtualization 537 Chapter 16 Presenting the Results 539 Report Basics 539 Creating a Narrative Report with Hyperlinks 542 Creating Hyperlinks 543 Creating and Linking Bookmarks 546 The Electronic Report Files 550 Creating Timelines 552 CaseMap and TimeMap 552 Splunk 555 Testifying about Technical Matters 560 The Bottom Line 562 Chapter 17 The Challenges of Cloud Computing and Virtualization 565 What Is Virtualization? 566 The Hypervisor 569 Preparing for Incident Response in Virtual Space 571 Forensic Analysis Techniques 575 Dead Host-Based Virtual Environment 576 Live Virtual Environment 584 Artifacts 586 Cloud Computing 587 What Is It? 587 Services 588 Forensic Challenges 589 Forensic Techniques 589 The Bottom Line 595 Part 5 Appendices 597 Appendix A The Bottom Line 599 Chapter 1: Network Investigation Overview 599 Chapter 2: The Microsoft Network Structure 601 Chapter 3: Beyond the Windows GUI 602 Chapter 4: Windows Password Issues 604 Chapter 5: Windows Ports and Services 606 Chapter 6: Live-Analysis Techniques 608 Chapter 7: Windows Filesystems 609 Chapter 8: The Registry Structure 611 Chapter 9: Registry Evidence 613 Chapter 10: Introduction to Malware 618 Chapter 11: Text-based Logs 620 Chapter 12: Windows Event Logs 622 Chapter 13: Logon and Account Logon Events 623 Chapter 14: Other Audit Events 624 Chapter 15: Forensic Analysis of Event Logs 626 Chapter 16: Presenting the Results 628 Chapter 17: The Challenges of Cloud Computing and Virtualization 630 Appendix B Test Environments 633 Software 633 Hardware 635 Setting Up Test Environments in Training Laboratories 636 Chapter 1: Network Investigation Overview 636 Chapter 2: The Microsoft Network Structure 636 Chapter 3: Beyond the Windows GUI 637 Chapter 4: Windows Password Issues 637 Chapter 5: Windows Ports and Services 639 Chapter 6: Live-Analysis Techniques 639 Chapter 7: Windows Filesystems 640 Chapter 8: The Registry Structure 640 Chapter 9: Registry Evidence 642 Chapter 10: Introduction to Malware 643 Chapter 11: Text-Based Logs 643 Chapter 12: Windows Event Logs 644 Chapter 13: Logon and Account Logon Events 644 Chapter 14: Other Audit Events 644 Chapter 15: Forensic Analysis of Event Logs 645 Chapter 16: Presenting the Results 645 Chapter 17: The Challenges of Cloud Computing and Virtualization 645 Index 647

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