{"product_id":"datadriven-security-9781118793725","title":"DataDriven Security","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003eUncover hidden patterns of data and respond with countermeasures\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSecurity professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful data analysis and visualization. You''ll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions.\u003c\/p\u003e \u003cp\u003eEverything in this book will have practical application for information security professionals.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eHelps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks\u003c\/li\u003e \u003cli\u003eIncludes more than a dozen real-world examples and hands-on exercises that demonstrate h\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eIntroduction xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 The Journey to Data-Driven Security 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA Brief History of Learning from Data 2\u003c\/p\u003e \u003cp\u003eNineteenth Century Data Analysis 2\u003c\/p\u003e \u003cp\u003eTwentieth Century Data Analysis 3\u003c\/p\u003e \u003cp\u003eTwenty-First Century Data Analysis 4\u003c\/p\u003e \u003cp\u003eGathering Data Analysis Skills 5\u003c\/p\u003e \u003cp\u003eDomain Expertise 6\u003c\/p\u003e \u003cp\u003eProgramming Skills 8\u003c\/p\u003e \u003cp\u003eData Management 10\u003c\/p\u003e \u003cp\u003eStatistics 12\u003c\/p\u003e \u003cp\u003eVisualization (aka Communication) 14\u003c\/p\u003e \u003cp\u003eCombining the Skills 15\u003c\/p\u003e \u003cp\u003eCentering on a Question 16\u003c\/p\u003e \u003cp\u003eCreating a Good Research Question 17\u003c\/p\u003e \u003cp\u003eExploratory Data Analysis 18\u003c\/p\u003e \u003cp\u003eSummary 18\u003c\/p\u003e \u003cp\u003eRecommended Reading 19\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Building Your Analytics Toolbox: A Primer on Using R and Python for Security Analysis 21\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhy Python? Why R? And Why Both? 22\u003c\/p\u003e \u003cp\u003eWhy Python? 23\u003c\/p\u003e \u003cp\u003eWhy R? 23\u003c\/p\u003e \u003cp\u003eWhy Both? 24\u003c\/p\u003e \u003cp\u003eJumpstarting Your Python Analytics with Canopy 24\u003c\/p\u003e \u003cp\u003eUnderstanding the Python Data Analysis and Visualization Ecosystem 25\u003c\/p\u003e \u003cp\u003eSetting Up Your R Environment 29\u003c\/p\u003e \u003cp\u003eIntroducing Data Frames 33\u003c\/p\u003e \u003cp\u003eOrganizing Analyses 36\u003c\/p\u003e \u003cp\u003eSummary 37\u003c\/p\u003e \u003cp\u003eRecommended Reading 38\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Learning the \"Hello World\" of Security Data Analysis 39\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSolving a Problem 40\u003c\/p\u003e \u003cp\u003eGetting Data41\u003c\/p\u003e \u003cp\u003eReading In Data 43\u003c\/p\u003e \u003cp\u003eExploring Data 47\u003c\/p\u003e \u003cp\u003eHoming In on a Question 58\u003c\/p\u003e \u003cp\u003eSummary 70\u003c\/p\u003e \u003cp\u003eRecommended Reading 70\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 Performing Exploratory Security Data Analysis 71\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDissecting the IP Address73\u003c\/p\u003e \u003cp\u003eRepresenting IP Addresses 73\u003c\/p\u003e \u003cp\u003eSegmenting and Grouping IP Addresses 75\u003c\/p\u003e \u003cp\u003eLocating IP Addresses 77\u003c\/p\u003e \u003cp\u003eAugmenting IP Address Data80\u003c\/p\u003e \u003cp\u003eAssociation\/Correlation, Causation, and Security Operations Center Analysts Gone Rogue 86\u003c\/p\u003e \u003cp\u003eMapping Outside the Continents90\u003c\/p\u003e \u003cp\u003eVisualizing the ZeuS Botnet 92\u003c\/p\u003e \u003cp\u003eVisualizing Your Firewall Data 98\u003c\/p\u003e \u003cp\u003eSummary 100\u003c\/p\u003e \u003cp\u003eRecommended Reading101\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 From Maps to Regression 103\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSimplifying Maps 105\u003c\/p\u003e \u003cp\u003eHow Many ZeroAccess Infections per Country? 108\u003c\/p\u003e \u003cp\u003eChanging the Scope of Your Data 111\u003c\/p\u003e \u003cp\u003eThe Potwin Effect 113\u003c\/p\u003e \u003cp\u003eIs This Weird? 117\u003c\/p\u003e \u003cp\u003eCounting in Counties 120\u003c\/p\u003e \u003cp\u003eMoving Down to Counties 122\u003c\/p\u003e \u003cp\u003eIntroducing Linear Regression 125\u003c\/p\u003e \u003cp\u003eUnderstanding Common Pitfalls in Regression Analysis 130\u003c\/p\u003e \u003cp\u003eRegression on ZeroAccess Infections 131\u003c\/p\u003e \u003cp\u003eSummary 136\u003c\/p\u003e \u003cp\u003eRecommended Reading 136\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Visualizing Security Data 137\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhy Visualize? 138\u003c\/p\u003e \u003cp\u003eUnraveling Visual Perception 139\u003c\/p\u003e \u003cp\u003eUnderstanding the Components of Visual Communications 144\u003c\/p\u003e \u003cp\u003eAvoiding the Third Dimension 144\u003c\/p\u003e \u003cp\u003eUsing Color 146\u003c\/p\u003e \u003cp\u003ePutting It All Together 148\u003c\/p\u003e \u003cp\u003eCommunicating Distributions 154\u003c\/p\u003e \u003cp\u003eVisualizing Time Series 156\u003c\/p\u003e \u003cp\u003eExperiment on Your Own 157\u003c\/p\u003e \u003cp\u003eTurning Your Data into a Movie Star 158\u003c\/p\u003e \u003cp\u003eSummary 159\u003c\/p\u003e \u003cp\u003eRecommended Reading 160\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Learning from Security Breaches 161\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSetting Up the Research 162\u003c\/p\u003e \u003cp\u003eConsiderations in a Data Collection Framework 164\u003c\/p\u003e \u003cp\u003eAiming for Objective Answers 164\u003c\/p\u003e \u003cp\u003eLimiting Possible Answers 164\u003c\/p\u003e \u003cp\u003eAllowing \"Other,\" and \"Unknown\" Options 164\u003c\/p\u003e \u003cp\u003eAvoiding Conflation and Merging the Minutiae 165\u003c\/p\u003e \u003cp\u003eAn Introduction to VERIS 166\u003c\/p\u003e \u003cp\u003eIncident Tracking 168\u003c\/p\u003e \u003cp\u003eThreat Actor 168\u003c\/p\u003e \u003cp\u003eThreat Actions 169\u003c\/p\u003e \u003cp\u003eInformation Assets 173\u003c\/p\u003e \u003cp\u003eAttributes 173\u003c\/p\u003e \u003cp\u003eDiscovery\/Response 176\u003c\/p\u003e \u003cp\u003eImpact 176\u003c\/p\u003e \u003cp\u003eVictim 177\u003c\/p\u003e \u003cp\u003eIndicators 179\u003c\/p\u003e \u003cp\u003eExtending VERIS with Plus 179\u003c\/p\u003e \u003cp\u003eSeeing VERIS in Action 179\u003c\/p\u003e \u003cp\u003eWorking with VCDB Data 181\u003c\/p\u003e \u003cp\u003eGetting the Most Out of VERIS Data 185\u003c\/p\u003e \u003cp\u003eSummary 189\u003c\/p\u003e \u003cp\u003eRecommended Reading 189\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Breaking Up with Your Relational Database 191\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eRealizing the Container Has Constraints 195\u003c\/p\u003e \u003cp\u003eConstrained by Schema 196\u003c\/p\u003e \u003cp\u003eConstrained by Storage 198\u003c\/p\u003e \u003cp\u003eConstrained by RAM 199\u003c\/p\u003e \u003cp\u003eConstrained by Data 200\u003c\/p\u003e \u003cp\u003eExploring Alternative Data Stores 200\u003c\/p\u003e \u003cp\u003eBerkeleyDB 201\u003c\/p\u003e \u003cp\u003eRedis 203\u003c\/p\u003e \u003cp\u003eHive 207\u003c\/p\u003e \u003cp\u003eMongoDB 210\u003c\/p\u003e \u003cp\u003eSpecial Purpose Databases 214\u003c\/p\u003e \u003cp\u003eSummary 215\u003c\/p\u003e \u003cp\u003eRecommended Reading 216\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Demystifying Machine Learning 217\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDetecting Malware 218\u003c\/p\u003e \u003cp\u003eDeveloping a Machine Learning Algorithm 220\u003c\/p\u003e \u003cp\u003eValidating the Algorithm 221\u003c\/p\u003e \u003cp\u003eImplementing the Algorithm 222\u003c\/p\u003e \u003cp\u003eBenefiting from Machine Learning 226\u003c\/p\u003e \u003cp\u003eAnswering Questions with Machine Learning 226\u003c\/p\u003e \u003cp\u003eMeasuring Good Performance 227\u003c\/p\u003e \u003cp\u003eSelecting Features 228\u003c\/p\u003e \u003cp\u003eValidating Your Model 230\u003c\/p\u003e \u003cp\u003eSpecific Learning Methods 230\u003c\/p\u003e \u003cp\u003eSupervised 231\u003c\/p\u003e \u003cp\u003eUnsupervised 234\u003c\/p\u003e \u003cp\u003eHands On: Clustering Breach Data 236\u003c\/p\u003e \u003cp\u003eMultidimensional Scaling on Victim Industries 238\u003c\/p\u003e \u003cp\u003eHierarchical Clustering on Victim Industries 240\u003c\/p\u003e \u003cp\u003eSummary 242\u003c\/p\u003e \u003cp\u003eRecommended Reading 243\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Designing Effective Security Dashboards 245\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhat Is a Dashboard, Anyway? 246\u003c\/p\u003e \u003cp\u003eA Dashboard Is Not an Automobile 246\u003c\/p\u003e \u003cp\u003eA Dashboard Is Not a Report 248\u003c\/p\u003e \u003cp\u003eA Dashboard Is Not a Moving Van 251\u003c\/p\u003e \u003cp\u003eA Dashboard Is Not an Art Show 253\u003c\/p\u003e \u003cp\u003eCommunicating and Managing \"Security\" through Dashboards 258\u003c\/p\u003e \u003cp\u003eLending a Hand to Handlers 258\u003c\/p\u003e \u003cp\u003eRaising Dashboard Awareness 260\u003c\/p\u003e \u003cp\u003eThe Devil (and Incident Response Delays) Is in the Details 262\u003c\/p\u003e \u003cp\u003eProjecting \"Security\" 263\u003c\/p\u003e \u003cp\u003eSummary 267\u003c\/p\u003e \u003cp\u003eRecommended Reading 267\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 Building Interactive Security Visualizations 269\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eMoving from Static to Interactive270\u003c\/p\u003e \u003cp\u003eInteraction for Augmentation 271\u003c\/p\u003e \u003cp\u003eInteraction for Exploration 274\u003c\/p\u003e \u003cp\u003eInteraction for Illumination 276\u003c\/p\u003e \u003cp\u003eDeveloping Interactive Visualizations 281\u003c\/p\u003e \u003cp\u003eBuilding Interactive Dashboards with Tableau 281\u003c\/p\u003e \u003cp\u003eBuilding Browser-Based Visualizations with D3 284\u003c\/p\u003e \u003cp\u003eSummary 294\u003c\/p\u003e \u003cp\u003eRecommended Reading 295\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 Moving Toward Data-Driven Security 297\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eMoving Yourself toward Data-Driven Security 298\u003c\/p\u003e \u003cp\u003eThe Hacker 299\u003c\/p\u003e \u003cp\u003eThe Statistician 302\u003c\/p\u003e \u003cp\u003eThe Security Domain Expert 302\u003c\/p\u003e \u003cp\u003eThe Danger Zone 303\u003c\/p\u003e \u003cp\u003eMoving Your Organization toward Data-Driven Security 303\u003c\/p\u003e \u003cp\u003eAsk Questions That Have Objective Answers 304\u003c\/p\u003e \u003cp\u003eFind and Collect Relevant Data 304\u003c\/p\u003e \u003cp\u003eLearn through Iteration 305\u003c\/p\u003e \u003cp\u003eFind Statistics 306\u003c\/p\u003e \u003cp\u003eSummary 308\u003c\/p\u003e \u003cp\u003eRecommended Reading 308\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A Resources and Tools 309\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix B References 313\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIndex 321\u003c\/b\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49406924390743,"sku":"9781118793725","price":36.09,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118793725.jpg?v=1730497577","url":"https:\/\/bookcurl.com\/products\/datadriven-security-9781118793725","provider":"Book Curl","version":"1.0","type":"link"}