3 papers
cs.CR2026
Discard the Dross and Select the Essential: Pre-query Sample Selection for Black-box Membership Inference Attacks
Dongdong Zhao, Jinrong Hu, Changtian Song +3
Black-box membership inference attacks (MIAs) rely on target-model queries to infer whether candidate samples were used for training. However, membership signals are highly non-uni…
cs.CV2025
Model Inversion Attack Against Deep Hashing
Dongdong Zhao, Qiben Xu, Ranxin Fang +1
Deep hashing improves retrieval efficiency through compact binary codes, yet it introduces severe and often overlooked privacy risks. The ability to reconstruct original training d…
cs.CR2025
Injection, Attack and Erasure: Revocable Backdoor Attacks via Machine Unlearning
Baogang Song, Dongdong Zhao, Jianwen Xiang +2
Backdoor attacks pose a persistent security risk to deep neural networks (DNNs) due to their stealth and durability. While recent research has explored leveraging model unlearning…