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Titlebook: Decision and Game Theory for Security; 9th International Co Linda Bushnell,Radha Poovendran,Tamer Ba?ar Conference proceedings 2018 Springe

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書目名稱Decision and Game Theory for Security
副標(biāo)題9th International Co
編輯Linda Bushnell,Radha Poovendran,Tamer Ba?ar
視頻videohttp://file.papertrans.cn/265/264324/264324.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Decision and Game Theory for Security; 9th International Co Linda Bushnell,Radha Poovendran,Tamer Ba?ar Conference proceedings 2018 Springe
描述The 28 revised full papers presented together with 8 short papers were carefully reviewed and selected from 44 submissions..Among the topical areas covered were: use of game theory; control theory; and mechanism design for security and privacy; decision making for cybersecurity and security requirements engineering; security and privacy for the Internet-of-Things; cyber-physical systems; cloud computing; resilient control systems, and critical infrastructure; pricing; economic incentives; security investments, and cyber insurance for dependable and secure systems; risk assessment and security risk management; security and privacy of wireless and mobile communications, including user location privacy; sociotechnological and behavioral approaches to security; deceptive technologies in cybersecurity and privacy; empirical and experimental studies with game, control, or optimization theory-based analysis for security and privacy; and adversarial machine learning and crowdsourcing, and the role of artificial intelligence in system security..
出版日期Conference proceedings 2018
關(guān)鍵詞game theory; security; privacy; decision making; control and mechanism design; optimization; probability; r
版次1
doihttps://doi.org/10.1007/978-3-030-01554-1
isbn_softcover978-3-030-01553-4
isbn_ebook978-3-030-01554-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/d/image/264324.jpg
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https://doi.org/10.1007/978-90-313-9129-5ic nature of losses. It is recognised that this information asymmetry may lead to a “market for lemons” in which suppliers face no incentive to provide higher quality products. Some security vendors have begun to offer cyber-warranties—voluntary ex-ante obligations to indemnify the customer in the e
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https://doi.org/10.1007/978-90-313-9129-5llicit machine learning classification task. Alice wants Bob (a machine learning system) to learn the task. However, sending either the training set or the trained model to Bob can raise suspicion if the communication is monitored. Training set camouflage allows Alice to compute a second training se
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https://doi.org/10.1007/978-90-313-9129-5 architecture or augmenting the training set with adversarial examples, but both have inherent limitations. Motivated by recent research that shows outliers in the training set have a high negative influence on the trained model, we studied the relationship between model robustness and the quality o
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