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Titlebook: Decision and Game Theory for Security; 11th International C Quanyan Zhu,John S. Baras,Juntao Chen Conference proceedings 2020 Springer Natu

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書(shū)目名稱Decision and Game Theory for Security
副標(biāo)題11th International C
編輯Quanyan Zhu,John S. Baras,Juntao Chen
視頻videohttp://file.papertrans.cn/265/264332/264332.mp4
叢書(shū)名稱Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Decision and Game Theory for Security; 11th International C Quanyan Zhu,John S. Baras,Juntao Chen Conference proceedings 2020 Springer Natu
描述This book constitutes the refereed proceedings of the 11th International Conference on Decision and Game Theory for Security, GameSec 2020,held in College Park, MD, USA, in October 2020. Due to COVID-19 pandemic the conference was held virtually?.The 21 full papers presented together with 2 short papers were carefully reviewed and selected from 29 submissions. The papers focus on machine learning and security; cyber deception; cyber-physical systems security; security of network systems; theoretic foundations of security games; emerging topics..
出版日期Conference proceedings 2020
關(guān)鍵詞artificial intelligence; computer crime; computer networks; computer science; computer security; computer
版次1
doihttps://doi.org/10.1007/978-3-030-64793-3
isbn_softcover978-3-030-64792-6
isbn_ebook978-3-030-64793-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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Learning and Planning in the Feature Deception Problemender’s loss by misleading the attacker to make suboptimal decisions. In order to formally reason about deception, we introduce the ., a domain-independent model and present a learning and planning framework for finding the optimal deception strategy, taking into account the adversary’s preferences
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Exploiting Bounded Rationality in Risk-Based Cyber Camouflage Games optimize a deceptive defense based on camouflaging network and system attributes, have shown effective numerical results on simulated data. However, these models possess a fundamental drawback due to the assumption that an attempted attack is always successful—as a direct consequence of the decepti
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