11 papers
Scratched Lenses, Shifted Depth: Passive Camera-Side Optical Attacks
Qinlin He, Zeming Zhuang, Yongji Wu +3
Physical adversarial attacks on vision systems are typically studied through scene manipulation, such as adversarial patches or projections, where the adversary controls what the c…
AdvScene: Rethinking Adversarial Patch Evaluation Through Scene Robustness
Xiaoyong, Yuan, Lan +1
Adversarial patches are physical patterns attached to real objects to mislead AI vision systems. Their real-world risk is not determined by a single successful prediction, but by w…
When AI Persuades: Adversarial Explanation Attacks on Human Trust in AI-Assisted Decision Making
Shutong Fan, Lan Zhang, Xiaoyong Yuan
Most adversarial threats in artificial intelligence (AI) target the computational behavior of models rather than the humans who rely on them. Yet modern AI systems increasingly ope…
Secure Semantic Communications via AI Defenses: Fundamentals, Solutions, and Future Directions
Lan Zhang, Chengsi Liang, Zeming Zhuang +4
Semantic communication (SemCom) redefines wireless communication from reproducing symbols to transmitting task-relevant semantics. However, this AI-native architecture also introdu…
Who's Wearing? Ear Canal Biometric Key Extraction for User Authentication on Wireless Earbuds
Chenpei Huang, Lingfeng Yao, Hui Zhong +5
Ear canal scanning/sensing (ECS) has emerged as a novel biometric authentication method for mobile devices paired with wireless earbuds. Existing studies have demonstrated the uniq…
Your RAG is Unfair: Exposing Fairness Vulnerabilities in Retrieval-Augmented Generation via Backdoor Attacks
Gaurav Bagwe, Saket S. Chaturvedi, Xiaolong Ma +3
Retrieval-augmented generation (RAG) enhances factual grounding by integrating retrieval mechanisms with generative models but introduces new attack surfaces, particularly through…