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Autonomous Cyber Deception [electronic resource] : Reasoning, Adaptive Planning, and Evaluation of HoneyThings /

Contributor(s): Material type: TextTextPublisher: Cham : Springer International Publishing : Imprint: Springer, 2019Edition: 1st ed. 2019Description: XII, 235 p. 79 illus., 65 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783030021108
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 005.8 23
LOC classification:
  • QA76.9.A25
Online resources:
Contents:
1 Using Deep Learning to Generate Relational HoneyData -- 2 Towards Intelligent Cyber Deception Systems -- 3 Honeypot Deception Tactics -- 4 Modeling and Analysis of Deception Games based on Hypergame Theory -- 5 Dynamic Bayesian Games for Adversarial and Defensive Cyber Deception -- 6 CONCEAL: A Strategy Composition for Resilient Cyber Deception - Framework, Metrics and Deployment -- 7 NetShifter - A Comprehensive Multi-Dimensional Network Obfuscation and Deception Solution -- 8 Deception-Enhanced Threat Sensing for Resilient Intrusion Detection -- 9 HONEYSCOPE: IoT Device Protection with Deceptive Network Views -- 10 gExtractor: Automated Extraction of Malware Deception Parameters for Autonomous Cyber Deception -- 11 Malware Deception with Automatic Analysis and Generation of HoneyResource.
In: Springer Nature eBookSummary: This textbook surveys the knowledge base in automated and resilient cyber deception. It features four major parts: cyber deception reasoning frameworks, dynamic decision-making for cyber deception, network-based deception, and malware deception. An important distinguishing characteristic of this book is its inclusion of student exercises at the end of each chapter. Exercises include technical problems, short-answer discussion questions, or hands-on lab exercises, organized at a range of difficulties from easy to advanced,. This is a useful textbook for a wide range of classes and degree levels within the security arena and other related topics. It’s also suitable for researchers and practitioners with a variety of cyber security backgrounds from novice to experienced.
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1 Using Deep Learning to Generate Relational HoneyData -- 2 Towards Intelligent Cyber Deception Systems -- 3 Honeypot Deception Tactics -- 4 Modeling and Analysis of Deception Games based on Hypergame Theory -- 5 Dynamic Bayesian Games for Adversarial and Defensive Cyber Deception -- 6 CONCEAL: A Strategy Composition for Resilient Cyber Deception - Framework, Metrics and Deployment -- 7 NetShifter - A Comprehensive Multi-Dimensional Network Obfuscation and Deception Solution -- 8 Deception-Enhanced Threat Sensing for Resilient Intrusion Detection -- 9 HONEYSCOPE: IoT Device Protection with Deceptive Network Views -- 10 gExtractor: Automated Extraction of Malware Deception Parameters for Autonomous Cyber Deception -- 11 Malware Deception with Automatic Analysis and Generation of HoneyResource.

This textbook surveys the knowledge base in automated and resilient cyber deception. It features four major parts: cyber deception reasoning frameworks, dynamic decision-making for cyber deception, network-based deception, and malware deception. An important distinguishing characteristic of this book is its inclusion of student exercises at the end of each chapter. Exercises include technical problems, short-answer discussion questions, or hands-on lab exercises, organized at a range of difficulties from easy to advanced,. This is a useful textbook for a wide range of classes and degree levels within the security arena and other related topics. It’s also suitable for researchers and practitioners with a variety of cyber security backgrounds from novice to experienced.

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