Autonomous Cyber Deception Reasoning, Adaptive Planning, and Evaluation of HoneyThings /
Autonomous Cyber Deception Reasoning, Adaptive Planning, and Evaluation of HoneyThings / [electronic resource] :
edited by Ehab Al-Shaer, Jinpeng Wei, Kevin W. Hamlen, Cliff Wang.
- 1st ed. 2019.
- XII, 235 p. 79 illus., 65 illus. in color. online resource.
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.
9783030021108
10.1007/978-3-030-02110-8 doi
Data protection.
Computer networks .
Artificial intelligence.
Application software.
Data and Information Security.
Computer Communication Networks.
Artificial Intelligence.
Computer and Information Systems Applications.
QA76.9.A25
005.8
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.
9783030021108
10.1007/978-3-030-02110-8 doi
Data protection.
Computer networks .
Artificial intelligence.
Application software.
Data and Information Security.
Computer Communication Networks.
Artificial Intelligence.
Computer and Information Systems Applications.
QA76.9.A25
005.8