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Titlebook: Computer Security – ESORICS 2023; 28th European Sympos Gene Tsudik,Mauro Conti,Georgios Smaragdakis Conference proceedings 2024 The Editor(

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書目名稱Computer Security – ESORICS 2023
副標(biāo)題28th European Sympos
編輯Gene Tsudik,Mauro Conti,Georgios Smaragdakis
視頻videohttp://file.papertrans.cn/234/233872/233872.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computer Security – ESORICS 2023; 28th European Sympos Gene Tsudik,Mauro Conti,Georgios Smaragdakis Conference proceedings 2024 The Editor(
描述.The four-volume set LNCS 14344-14347 constitutes the refereed proceedings of the 28th European Symposium on Research in Computer Security, ESORICS 2023, which took place in The Hague, The Netherlands, during September 25-29, 2023...The 93 full papers presented in these proceedings were carefully reviewed and selected from?478?submissions. They were organized in topical sections as follows:.Part I: Crypto...Part II:?Network, web and internet; privacy; and remote...Part III: Attacks; blockchain; and miscellaneous..Part IV: Machine learning; software and systems security..
出版日期Conference proceedings 2024
關(guān)鍵詞access control; authentication; computer crime; cryptography; data security; databases
版次1
doihttps://doi.org/10.1007/978-3-031-51482-1
isbn_softcover978-3-031-51481-4
isbn_ebook978-3-031-51482-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Reinforcement Learning Approach to?Generate Zero-Dynamics Attacks on?Control Systems Without State Se space. We develop several attackers and detectors iteratively until the attacker and detectors no longer improve. In addition, we also show that the reinforcement learning based attacker successfully executes an attack in the same manner as the theoretical attacker described in previous literature.
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DScope: To Reliably and?Securely Acquire Live Data from?Kernel-Compromised ARM Devicesdevelopment board and have also tested . ’s reliability against various forms of denial of service attacks. Our experiments show that a user can dynamically import data acquisition routines to the device to extract kernel objects and runtime stacks from an attack scene or a kernel crashing site.
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PassGPT: Password Modeling and (Guided) Generation with Large Language Modelsre we leverage PassGPT sampling procedure to generate passwords matching arbitrary constraints, a feat lacking in current GAN-based strategies. Lastly, we conduct an in-depth analysis of the entropy and probability distribution that PassGPT defines over passwords and discuss their use in enhancing existing password strength estimators.
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