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Game theory and machine learning for cyber security / edited by Charles A. Kamhoua, Christopher D. Kiekintveld, Fei Fang, Quanyan Zhu.

Contributor(s): Kamhoua, Charles A [editor.] | Kiekintveld, Christopher D [editor.] | Fang, Fei, 1989- [editor.] | Zhu, Quanyan [editor.].
Material type: materialTypeLabelBookPublisher: Hoboken, New Jersey : John Wiley & Sons, Inc., [2021]Description: 1 online resource : illustrations (chiefly color).Content type: text Media type: computer Carrier type: online resourceISBN: 1119723949; 9781119723912; 1119723914; 9781119723950; 1119723957; 9781119723943.Subject(s): Computer networks -- Security measures | Game theory | Machine learning | Computer networks -- Security measures | Game theory | Machine learningGenre/Form: Electronic books.Additional physical formats: Print version:: Game theory and machine learning for cyber securityDDC classification: 658.4/78 Online resources: Wiley Online Library
Partial contents:
Introduction to game theory / Fei Fang, Shutian Liu, Anjon Basak, Quanyan Zhu, Christopher Kiekintveld, Charles A. Kamhoua -- Scalable algorithms for identifying stealthy attackers in a game theoretic framework using deception / Anjon Basak, Charles Kamhoua, Sridhar Venkatesan, Marcus Gutierrez, Ahmed H. Anwar, Christopher Kiekintveld -- Honeypot allocation game over attack graphs for cyber deception / Ahmed H. Anwar, Charles Kamhoua, Nandi Leslie, Christopher Kiekintveld.
Summary: "Cyber security is a serious concern to our economic prosperity and national security. Despite an increased investment in cyber defense, cyber-attackers are becoming more creative and sophisticated. This exposes the need for a more rigorous approach to cyber security, including methods from artificial intelligence including computational game theory and machine learning. Recent advances in adversarial machine learning are promising to make artificial intelligence (AI) algorithms more robust to deception and intelligent manipulation. However, they are still vulnerable to adversarial inputs, data poisoning, model stealing and evasion attacks. The above challenges and the high risk and consequence of cyber-attacks drive the need to accelerate basic research on cyber security"-- Provided by publisher.
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Includes bibliographical references and index.

Introduction to game theory / Fei Fang, Shutian Liu, Anjon Basak, Quanyan Zhu, Christopher Kiekintveld, Charles A. Kamhoua -- Scalable algorithms for identifying stealthy attackers in a game theoretic framework using deception / Anjon Basak, Charles Kamhoua, Sridhar Venkatesan, Marcus Gutierrez, Ahmed H. Anwar, Christopher Kiekintveld -- Honeypot allocation game over attack graphs for cyber deception / Ahmed H. Anwar, Charles Kamhoua, Nandi Leslie, Christopher Kiekintveld.

"Cyber security is a serious concern to our economic prosperity and national security. Despite an increased investment in cyber defense, cyber-attackers are becoming more creative and sophisticated. This exposes the need for a more rigorous approach to cyber security, including methods from artificial intelligence including computational game theory and machine learning. Recent advances in adversarial machine learning are promising to make artificial intelligence (AI) algorithms more robust to deception and intelligent manipulation. However, they are still vulnerable to adversarial inputs, data poisoning, model stealing and evasion attacks. The above challenges and the high risk and consequence of cyber-attacks drive the need to accelerate basic research on cyber security"-- Provided by publisher.

Description based on online resource; title from digital title page (viewed on September 29, 2021).

Wiley Frontlist Obook All English 2021

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