Author

Zizhuang Deng

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Open access Jul 2026

CAFAD: common acoustic features for adversarial audio detection

CAFAD is proposed, a plug-and-play detection framework that combines multi-domain acoustic feature fusion and temporal pyramid matching for variable-length adversarial audio detection that achieves an average detection accuracy of 99.25%, with a false positive rate of 1.00% on benign samples.

Wenjie Li, Pengyu Wei, Xuejing Yuan et al. · Cybersecurity · 0 citations

#small language model Preprint Aug 2026

Beyond Vector Hiding: Breaking and Mitigating Shared-Direction Weight Obfuscation in TEE-Offloaded Large Language Models

This work identifies shared rank-one reuse as the root cause of the leakage exploited by the authors' attacks, and proposes LatticeLeak, which exploits the resulting hidden lattice.

Mengxia Zhang, Ao-Ying Zheng, Guo-Xiao Liu et al. · 0 citations