Dynamic Games for Network Security

Particularly, the exposition of this book begins with a brief introduction of relevant background knowledge in Chapter 1, followed by a review of existing applications of SG in addressing various dynamic network security problems in Chapter ...

Dynamic Games for Network Security

Dynamic Games for Network Security

The goal of this SpringerBrief is to collect and systematically present the state-of-the-art in this research field and the underlying game-theoretic and learning tools to the broader audience with general network security and engineering backgrounds. Particularly, the exposition of this book begins with a brief introduction of relevant background knowledge in Chapter 1, followed by a review of existing applications of SG in addressing various dynamic network security problems in Chapter 2. A detailed treatment of dynamic security games with information asymmetry is given in Chapters 3–5. Specifically, dynamic security games with extra information that concerns security competitions, where the defender has an informational advantage over the adversary are discussed in Chapter 3. The complementary scenarios where the defender lacks information about the adversary is examined in Chapter 4 through the lens of incomplete information SG. Chapter 5 is devoted to the exploration of how to proactively create information asymmetry for the defender’s benefit. The primary audience for this brief includes network engineers interested in security decision-making in dynamic network security problems. Researchers interested in the state-of-the-art research on stochastic game theory and its applications in network security will be interested in this SpringerBrief as well. Also graduate and undergraduate students interested in obtaining comprehensive information on stochastic game theory and applying it to address relevant research problems can use this SpringerBrief as a study guide. Lastly, concluding remarks and our perspective for future works are presented in Chapter 6.

More Books:

Dynamic Games for Network Security
Language: en
Pages: 74
Authors: Xiaofan He, Huaiyu Dai
Categories: Technology & Engineering
Type: BOOK - Published: 2018-02-28 - Publisher: Springer

The goal of this SpringerBrief is to collect and systematically present the state-of-the-art in this research field and the underlying game-theoretic and learning tools to the broader audience with general network security and engineering backgrounds. Particularly, the exposition of this book begins with a brief introduction of relevant background knowledge
Game Theory and Machine Learning for Cyber Security
Language: en
Pages: 544
Authors: Charles A. Kamhoua, Christopher D. Kiekintveld, Fei Fang, Quanyan Zhu
Categories: Technology & Engineering
Type: BOOK - Published: 2021-09-15 - Publisher: John Wiley & Sons

Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory
Game Theory for Security and Risk Management
Language: en
Pages: 418
Authors: Stefan Rass, Stefan Schauer
Categories: Mathematics
Type: BOOK - Published: 2018-07-06 - Publisher: Springer

The chapters in this volume explore how various methods from game theory can be utilized to optimize security and risk-management strategies. Emphasizing the importance of connecting theory and practice, they detail the steps involved in selecting, adapting, and analyzing game-theoretic models in security engineering and provide case studies of successful
Optimization and Dynamics with Their Applications
Language: en
Pages: 344
Authors: Akio Matsumoto
Categories: Mathematics
Type: BOOK - Published: 2017-05-23 - Publisher: Springer

This book presents a variety of advanced research papers in optimization and dynamics written by internationally recognized researchers in these fields. As an example of applying optimization in sport, it introduces a new method for finding the optimal bat sizes in baseball and softball. The book is divided into three
Machine Learning for Cyber Security
Language: en
Pages: 398
Authors: Xiaofeng Chen, Xinyi Huang, Jun Zhang
Categories: Computers
Type: BOOK - Published: 2019-09-11 - Publisher: Springer Nature

This book constitutes the proceedings of the Second International Conference on Machine Learning for Cyber Security, ML4CS 2019, held in Xi’an, China in September 2019. The 23 revised full papers and 3 short papers presented were carefully reviewed and selected from 70 submissions. The papers detail all aspects of machine

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