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Universal Defensive Underpainting Patch: Making Your Text Invisible to Optical Character Recognition.

, , , , , , , and . ACM Multimedia, page 7559-7568. ACM, (2023)

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Hijacking Attacks against Neural Network by Analyzing Training Data., , , , , , , , , and . USENIX Security Symposium, USENIX Association, (2024)More Simplicity for Trainers, More Opportunity for Attackers: Black-Box Attacks on Speaker Recognition Systems by Inferring Feature Extractor., , , , , , , , and . USENIX Security Symposium, USENIX Association, (2024)Universal Defensive Underpainting Patch: Making Your Text Invisible to Optical Character Recognition., , , , , , , and . ACM Multimedia, page 7559-7568. ACM, (2023)Privacy-Preserving Collaborative Deep Learning with Unreliable Participants., , , , and . CoRR, (2018)Privacy-Preserving Collaborative Deep Learning With Unreliable Participants., , , , and . IEEE Trans. Inf. Forensics Secur., (2020)Zero-Query Adversarial Attack on Black-box Automatic Speech Recognition Systems., , , , , , , , and . CoRR, (2024)Hijacking Attacks against Neural Networks by Analyzing Training Data., , , , , , , , , and . CoRR, (2024)Revisiting Adversarial Training under Long-Tailed Distributions., , , and . CoRR, (2024)FastTextDodger: Decision-Based Adversarial Attack Against Black-Box NLP Models With Extremely High Efficiency., , , , , , and . IEEE Trans. Inf. Forensics Secur., (2024)Enhancing Adversarial Transferability Through Neighborhood Conditional Sampling., , , and . CoRR, (2024)