Usenix Security '23 - Patrol: Provable Defense Against Adversarial Policy In Two-Player Games

USENIX Security '23 - PATROL: Provable Defense against Adversarial Policy in Two-player Games

USENIX Security '23 - Evading Provenance-Based ML Detectors with Adversarial System Action

USENIX Security '21 - PatchGuard: A Provably Robust Defense against Adversarial Patches via Small

USENIX Security '24 - Correction-based Defense Against Adversarial Video Attacks via...

USENIX Security '23 - The Space of Adversarial Strategies

USENIX Security '21 - Adversarial Policy Training against Deep Reinforcement Learning

USENIX Security '23 - Towards Targeted Obfuscation of Adversarial Unsafe Images using...

USENIX Security '22 - PatchCleanser: Certifiably Robust Defense against Adversarial Patches...

USENIX Security '23 - QFA2SR: Query-Free Adversarial Transfer Attacks to Speaker Recognition Systems

USENIX Security '23 - NeuroPots: Realtime Proactive Defense against Bit-Flip Attacks in Neural...

USENIX Security '21 - Dirty Road Can Attack: Security of Deep Learning based Automated Lane

USENIX Security '24 - PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation...

USENIX Security '23 - CAPatch: Physical Adversarial Patch against Image Captioning Systems

USENIX Security '23 - UnGANable: Defending Against GAN-based Face Manipulation

USENIX Security '19 - Lessons Learned from Evaluating the Robustness of Defenses to

USENIX Security '23 - Aegis: Mitigating Targeted Bit-flip Attacks against Deep Neural Networks

USENIX Security '24 - Defending Against Data Reconstruction Attacks in Federated Learning: An...

USENIX Security '24 - Splitting the Difference on Adversarial Training

USENIX Security '21 - T-Miner: A Generative Approach to Defend Against Trojan Attacks on DNN-based