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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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楼主: foresight
发表于 2025-3-26 23:18:46 | 显示全部楼层
Aion: Secure Transaction Ordering Using TEEsroadcast their commands to all processes. This is impractical due to the impact on scalability, and thus it discourages the adoption of a fair ordering of commands. Alternative approaches to order-fairness allow clients do send their commands to only one process, but provide a weaker notion of order
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https://doi.org/10.1007/978-3-642-11273-7t grids, and vehicular networks. This paper investigates a subset of stealthy attacks known as zero-dynamics-based stealthy attacks. While previous works on zero-dynamics attacks have highlighted the necessity of highly accurate knowledge of the system’s state space for generating attack signals, ou
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https://doi.org/10.1007/978-3-642-11273-7 However, machine learning models are susceptible to adversarial attacks, requiring the testing of model and product robustness. Meanwhile, attackers also seek to automate malware generation and evasion of antivirus systems, and defenders try to gain insight into their methods. This work proposes a
发表于 2025-3-27 20:13:00 | 显示全部楼层
https://doi.org/10.1007/978-3-642-11273-7ir private training datasets. Therefore, without revealing the private dataset, the clients can obtain a deep learning (DL) model with high performance. However, recent research proposed poisoning attacks that cause a catastrophic loss in the accuracy of the global model when adversaries, posed as b
发表于 2025-3-27 23:00:52 | 显示全部楼层
https://doi.org/10.1007/978-3-642-11273-7r study funded by Germany’s Federal Office for Information Security (BSI). SAST describes the practice of applying static analysis techniques to program code on the premise of detecting security-critical software defects early during the development process. In the past, this was done by using rule-
发表于 2025-3-28 05:12:29 | 显示全部楼层
The Disintegration of the American Empirese attacks against the next word prediction model used in Google’s GBoard app, a widely used mobile keyboard app that has been an early adopter of federated learning for production use. We demonstrate that the words a user types on their mobile handset, e.g. when sending text messages, can be recover
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