Fushuo Huo
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PrismWF introduces a multi-granularity patch-based Transformer to significantly improve website fingerprinting attacks by effectively modeling complex, mixed-traffic patterns from multi-tab browsing sessions.
The paper proposes TimeGuard, a novel channel-wise pool training defense, to significantly improve the robustness of time series forecasting against backdoor attacks by addressing signal dilution and loss degeneration.
A post-retrieval defense, GuardRAG, is proposed to mitigate corpus poisoning attacks on Large Language Models.
Papers
GuardRAG: A Post-Retrieval Defense against Poisoning Attacks in Retrieval-Augmented Generation
Linghui Jiao, Kang Wei, Fushuo Huo, Ruijie Zhao +4 more
A post-retrieval defense, GuardRAG, is proposed to mitigate corpus poisoning attacks on Large Language Models.