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Applied Security Visualization

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Prefacep. xiii
Acknowledgmentsp. xix
About the Authorp. xxiii
Visualizationp. 1
What Is Visualization?p. 2
Why Visualization?p. 3
Visualization Benefitsp. 5
Security Visualizationp. 6
Security Visualization's Dichotomyp. 7
Visualization Theoryp. 8
Perceptionp. 9
Expressive and Effective Graphsp. 11
Graph Design Principlesp. 13
Information Seeking Mantrap. 18
Summaryp. 19
Data Sourcesp. 21
Terminologyp. 22
Security Datap. 23
Common Problemsp. 24
Incomplete Informationp. 25
Source/Destination Confusionp. 26
Packet Capturesp. 27
Traffic Flowsp. 30
Collecting Traffic Flowsp. 32
Aggregating Traffic Flowsp. 35
Clustering Traffic Flowsp. 36
Anonymizing Traffic Flowsp. 36
Firewallsp. 37
Intrusion Detection and Prevention Systemsp. 40
Passive Network Analysisp. 43
Operating Systemsp. 45
Real-Time Operating System Informationp. 46
Operating System State Informationp. 49
Operating System Log Problemsp. 53
Applicationsp. 55
Web Proxyp. 56
Mailp. 58
Databasesp. 60
Configurationsp. 62
Summaryp. 64
VisuallyRepresenting Datap. 65
Graph Propertiesp. 66
Data Typesp. 66
Colorp. 68
Size, Shape, and Orientationp. 69
Chart Axesp. 69
Simple Chartsp. 70
Pie Chartp. 71
Bar Chartp. 72
Line Chartp. 73
3D Bar Chartsp. 74
Stacked Chartsp. 75
Stacked Pie Chartp. 76
Stacked Bar Chartp. 77
Stacked Line Chartp. 78
Histogramsp. 78
Box Plotsp. 80
Scatter Plotsp. 82
Parallel Coordinatesp. 85
Link Graphsp. 87
Mapsp. 93
Treemapsp. 96
Three-Dimensional Viewsp. 100
Three-Dimensional Scatter Plotsp. 101
Three-Dimensional Link Graphsp. 103
Interaction and Animationp. 104
Interactionp. 104
Animationp. 105
Choosing the Right Graphp. 109
Challengesp. 115
Summaryp. 117
From Data to Graphsp. 119
Information Visualization Processp. 119
Define the Problemp. 121
Assess Available Datap. 122
Process Informationp. 124
Adding Additional Datap. 126
Filtering Log Entriesp. 127
Aggregationp. 128
Data Processing Challengesp. 129
Visual Transformationp. 132
Data Mappingp. 132
Size and Shapep. 137
Colorp. 140
View Transformationp. 143
Aggregationp. 144
Interpret and Decidep. 146
Tools for Data Processingp. 150
Excel, OpenOffice, and Text Editorsp. 151
Regular Expressionsp. 151
UNIX toolsp. 152
Perlp. 155
Parsersp. 157
Other Toolsp. 158
Summaryp. 158
Visual Security Analysisp. 161
Reportingp. 162
Reporting Toolsp. 164
Issues and Problemsp. 165
Reporting Machine Access-An Examplep. 165
Historical Analysisp. 169
Time-Series Visualizationp. 169
Correlation Graphsp. 189
Interactive Analysisp. 192
Forensic Analysisp. 197
Real-Time Monitoring and Analysisp. 228
Dashboardsp. 228
Situational Awarenessp. 236
Summaryp. 237
Perimeter Threatp. 239
Traffic-Flow Monitoring and Analysisp. 240
Service Characteristicsp. 240
Service Anomaliesp. 245
Worm Detectionp. 250
Denial of Servicep. 254
Botnetsp. 257
Policy-Based Traffic-Flow Analysisp. 264
Firewall Log Analysisp. 268
Firewall Visualization Processp. 268
Firewall Ruleset Analysisp. 272
Intrusion Detection System Signature Tuningp. 278
Wireless Sniffingp. 286
Email Data Analysisp. 290
Email Server Analysisp. 291
Social Network Analysisp. 298
Vulnerability Data Visualizationp. 302
Risk-Posture Visualizationp. 304
Vulnerability-Posture Changesp. 310
Summaryp. 312
Compliancep. 315
Policies, Objectives, and Controlsp. 316
Regulations and Industry Mandatesp. 318
IT Control Frameworksp. 322
Logging Requirementsp. 324
Auditp. 328
Audit Data Visualizationp. 332
Business Process Monitoringp. 333
Compliance Monitoringp. 338
Risk Managementp. 343
Control Objective Prioritizationp. 345
Risk Visualizationp. 346
Separation of Dutiesp. 356
An Example of Applying Visualization to an SoD Auditp. 357
Generating SoD Graphsp. 360
Database Monitoringp. 362
Summaryp. 370
Insider Threatp. 373
Insider Threat Visualizationp. 374
What Is a Malicious Insider?p. 374
Three Types of Insider Crimesp. 375
Information Theftp. 376
Fraudp. 382
Sabotagep. 387
Who Are the Malicious Insiders?p. 390
Information Theftp. 390
Fraudsterp. 391
Saboteurp. 391
A Detection Framework for Malicious Insidersp. 392
Precursorsp. 392
Assigning Scores to Precursorsp. 394
Insider-Detection Processp. 396
Summary of Insider-Detection Processp. 408
Insider-Detection Process at Workp. 409
Improved Insider-Detection Processp. 414
Watch Listsp. 415
Adding Watch Lists to the Insider-Detection Processp. 419
Grouping Precursors into Bucketsp. 420
Candidate Graph Based on Precursor Bucketsp. 422
Improved Insider-Detection Process Summaryp. 424
Extended Insider-Detection Process at Workp. 424
Challengesp. 431
Proactive Mitigationp. 432
Sample Precursorsp. 433
Summaryp. 444
Data Visualization Toolsp. 445
Data Inputsp. 446
Comma Separated Valuesp. 446
TM3p. 447
DOTp. 448
GMLp. 449
Freely Available Visualization Toolsp. 450
Static Data Graphsp. 451
Stand-Alone Applicationsp. 464
Open Source Visualization Librariesp. 492
Java Librariesp. 493
Non-Java Librariesp. 494
Charting Librariesp. 495
Libraries Summaryp. 496
Online Toolsp. 497
Swivelp. 498
Many Eyesp. 499
Google Maps and Google Earthp. 499
Google Chart APIp. 501
Commercial Visualization Toolsp. 502
Advizorp. 502
Other Commercial Visualization Toolsp. 504
Summaryp. 505
Indexp. 507
Table of Contents provided by Ingram. All Rights Reserved.

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APPLIED SECURITY VISUALIZATION ldquo;Collecting log data is one thing, having relevant information is something else. The art to transform all kinds of log data into meaningful security information is the core of this book. Raffy illustrates in a straight forward way, and with hands-on examples, how such a challenge can be mastered. Let's get inspired.rdquo; Andreas Wuchner, Head of Global IT Security, Novartis Use Visualization to Secure Your Network Against the Toughest, Best-Hidden Threats As networks become ever more complex, securing them becomes more and more difficult. The solution is visualization. Using todayrsquo;s state-of-the-art data visualization techniques, you can gain a far deeper understanding of whatrsquo;s happening on your network right now. You can uncover hidden patterns of data, identify emerging vulnerabilities and attacks, and respond decisively with countermeasures that are far more likely to succeed than conventional methods. InApplied Security Visualization, leading network security visualization expert Raffael Marty introduces all the concepts, techniques, and tools you need to use visualization on your network. Yoursquo;ll learn how to identify and utilize the right data sources, then transform your data into visuals that reveal what you really need to know. Next, Marty shows how to use visualization to perform broad network security analyses, assess specific threats, and even improve business compliance. He concludes with an introduction to a broad set of visualization tools. The bookrsquo;s CD also includes DAVIX, a compilation of freely available tools for security visualization. You'll learn how to: bull; Intimately understand the data sources that are essential for effective visualization bull; Choose the most appropriate graphs and techniques for your IT data bull; Transform complex data into crystal-clear visual representations bull; Iterate your graphs to deliver even better insight for taking action bull; Assess threats to your network perimeter, as well as threats imposed by insiders bull; Use visualization to manage risks and compliance mandates more successfully bull; Visually audit both the technical and organizational aspects of information and network security bull; Compare and master todayrsquo;s most useful tools for security visualization Contains the live CD Data Analysis and Visualization Linux (DAVIX). DAVIX is a compilation of powerful tools for visualizing networks and assessing their security. DAVIX runs directly from the CD-ROM, without installation. Raffael Martyis chief security strategist and senior product manager for Splunk, the leading provider of large-scale, high-speed indexing and search technology for IT infrastructures. As customer advocate and guardian, he focuses on using his skills in data visualization, log management, intrusion detection, and compliance. An active participant on industry standards committees such as CEE (Common Event Expression) and OVAL (Open Vulnerability and Assessment Language), Marty created the Thor and AfterGlow automation tools, and founded the security visualization portal secviz.org. Before joining Splunk, he managed the solutions team at ArcS

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