Buch, Englisch, 304 Seiten, Format (B × H): 203 mm x 251 mm, Gewicht: 703 g
A Cyber-Behavioral Science Approach
Buch, Englisch, 304 Seiten, Format (B × H): 203 mm x 251 mm, Gewicht: 703 g
ISBN: 978-1-394-38150-0
Verlag: Wiley
Apply cyber behavioral science methods to network analysis and digital investigations
Digital investigations require specialized cyberpsychological expertise to interpret network behavior and identify meaningful patterns. Advanced Network Forensics provides forensic professionals with rigorous analytical frameworks for examining digital evidence through a cyberpsychological lens. Marshall S. Rich of Rich on Cyber presents cyber behavioral science methodologies that connect traditional forensic psychology principles with contemporary network investigation challenges facing practitioners today.
The book delivers systematic approaches for analyzing network activity, interpreting digital behavioral patterns, and constructing psychologically informed investigative narratives. Readers gain practical tools for applying forensic cyberpsychology concepts to network environments, understanding threat actor behavior, and developing evidence-based conclusions. Each chapter builds competencies essential for professionals working at the intersection of psychology and digital forensics.
Readers will also find:
- Frameworks for integrating cyberpsychological assessment principles with network forensic investigation methodologies and digital evidence analysis procedures
- Techniques for interpreting online behavioral patterns and constructing psychologically grounded profiles of network threat actors
- Protocols for documenting forensic findings in formats suitable for legal proceedings, organizational reports, and interdisciplinary collaboration
- Methods for evaluating the reliability and validity of network-derived psychological evidence in investigative contexts
- Strategies for maintaining objectivity and applying ethical standards when conducting cyberpsychologically informed digital forensic examinations
Advanced Network Forensics serves forensic psychologists, digital investigators, cybersecurity professionals, and researchers who require evidence-based cyber behavioral science frameworks for network analysis. The book equips practitioners with rigorous methodologies for applying forensic expertise to increasingly complex digital investigative environments.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Descriptive Outline of Advanced Behavior viii
Why this Book Is Urgent xii
Preface xiv
Acronyms and Key Terms xix
PART ONE Foundations of Advanced Network Forensics Using a Cyber-Behavioral Science Approach
CHAPTER 1 Introduction to Advanced Network Forensics 3
Introduces the shift from reactive, artifact-centric forensics to behavior-based, interdisciplinary models that blend cyberpsychology, ML/AI, and legal-ethical frameworks.
CHAPTER 2 Fundamentals of Network Forensics and Log Analysis 23
Establishes the core concepts, data sources, and workflows for packet, flow, and log forensics, including capture, DPI, parsing, and evidence preservation.
CHAPTER 3 Building a Network Forensics Lab Environment 44
Guides the design of a safe, high-fidelity network forensics lab for adversary emulation, realistic traffic generation, and legally defensible evidence handling.
PART TWO Human Factors and Behavioral Intelligence
CHAPTER 4 Behavioral Analysis in Cybersecurity 69
Explores forensic cyberpsychology, profiling, emotion, and group dynamics to understand and anticipate the human factors driving cyber threats.
CHAPTER 5 Cyber Forensics Behavioral Analysis (CFBA) 87
Presents the CFBA model, integrating behavioral science, digital forensics, and ML-driven scoring (CBAM/CBS) to predict and attribute cyber threats.
PART THREE Advanced Techniques, Tools, and AI
CHAPTER 6 Advanced Techniques and Tools 107
Details advanced behavioral defenses such as deception networks, honeypots, DPI/NTA, insider-threat analytics, and psychological profiling for proactive threat hunting.
CHAPTER 7 Machine Learning and Artificial Intelligence in Forensics 124
Examines unsupervised anomaly detection, time-series forecasting, MAESTRO, and XAI as AI/ML building blocks for proactive, behavior-based forensic workflows.
PART FOUR Behavioral Telemetry, SIEM, and Log Pipelines
CHAPTER 8 SIEM Configuration for Behavioral Log Collection 149
Shows how to configure SIEM and UEBA using standardized telemetry, enrichment, ML baselines, and SOAR to support behavior-driven detection at scale.
CHAPTER 9 Collecting Log Streams from Enterprise, Edge, Honeypots, and Authentication Logs 163
Describes hybrid log-collection strategies across enterprise, edge, honeypots, and identity systems, including AI-powered honeypots and tiered storage models.
CHAPTER 10 Correlation and Investigation within SIEM 182
Explains AI-driven SIEM correlation and investigation, combining UEBA, ML, NLP, and SOAR playbooks to automate triage and shorten MTTD/MTTR.
PART FIVE Domains and Applied Behavioral Forensics
CHAPTER 11 Specialized Forensics by Domain 203
Surveys domain-specific forensic frameworks and behavioral indicators for ICS/SCADA, IoT, cloud, storage, smart cities, healthcare, and interdependent infrastructures.
CHAPTER 12 Case Studies in Advanced Behavior-Based Network Forensics 219
Uses real-world case studies to show CFBA, ABS, and CBFM in action, demonstrating how behavior-driven analytics reduce dwell time and prevent full-scale breaches.
PART SIX Futures, Strategy, and Emerging Paradigms
CHAPTER 13 The Future of Network Forensics and Cyberpsychology 237
Looks ahead to AI-scaled evidence processing, adaptive deception (SPADE), cognitive forensics, quantum-enabled analysis, and emerging ethical and legal standards.
Glossary of Technical and Behavioral Terms 249
References 252
Index 267




