Titlebook: Computer Security – ESORICS 2024; 29th European Sympos Joaquin Garcia-Alfaro,Rafa? Kozik,Sokratis Katsika Conference proceedings 2024 The E

只看該作者 · 發(fā)表于 2025-3-23 23:23:47

Meili Cao,Haizhen He,Rongming Luo,Lei Wennce, they are costly and lack flexibility. Software-based defenses, on the other hand, provide flexibility but suffer from low performance. Recently, programmable switches have emerged and present an opportunity for efficient in-network defenses against DDoS attacks at line speed. Unfortunately, mos

只看該作者 · 發(fā)表于 2025-3-24 02:23:38

Mingwu Zhang,Biwen Chen,Hua Shentnerships between network operators allow requesting authentication vectors. This feature opens doors for state-sponsored attackers with access to roaming infrastructure, allowing the operation of stealthy RBSes anywhere in the world. This by far exceeds what lawful interception interfaces were desi

只看該作者 · 發(fā)表于 2025-3-24 07:31:57

Yu Ji,Youhui Zhang,He Liu,Weimin Zhengeration suffers from poor scalability due to their combinatorial complexity. Current solutions propose to address the generation problem from the algorithmic perspective and postulate the analysis only after the generation is complete, thus implying too long waiting time before enabling analysis cap

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只看該作者 · 發(fā)表于 2025-3-24 16:47:21

Rijun Cai,Weigang Wu,Ning Huang,Lihui Wucy concerns due to their strong inference potential. In this work, we propose TUL-STEO, a novel deep learning approach, based on a combination of pretraining and fine-tuning, for performing a Trajectory-User Linking (TUL) attack (also called user re-identification attack). More precisely, TUL-STEO c

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