NDSS 2025 - Defending against Backdoor Attacks on Graph Neural Networks via Discrepancy Learning

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NDSS 2025 - Defending Against Membership Inference Attacks on Iteratively Pruned Deep Neural Network NDSS 2025 - Defending Against Membership Inference Attacks on Iteratively Pruned Deep Neural Network
NDSS 2025 - SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning NDSS 2025 - SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning
NDSS 2025 - BitShield: Defending Against Bit-Flip Attacks on DNN Executables NDSS 2025 - BitShield: Defending Against Bit-Flip Attacks on DNN Executables
NDSS 2025 - CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling NDSS 2025 - CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling
NDSS 2023 - BEAGLE: Forensics of Deep Learning Backdoor Attack for Better Defense NDSS 2023 - BEAGLE: Forensics of Deep Learning Backdoor Attack for Better Defense
NDSS 2025 - PBP: Post-training Backdoor Purification for Malware Classifiers NDSS 2025 - PBP: Post-training Backdoor Purification for Malware Classifiers
NDSS 2025 - LADDER: Multi-Objective Backdoor Attack via Evolutionary Algorithm NDSS 2025 - LADDER: Multi-Objective Backdoor Attack via Evolutionary Algorithm
NDSS 2024 - TextGuard: Provable Defense against Backdoor Attacks on Text Classification NDSS 2024 - TextGuard: Provable Defense against Backdoor Attacks on Text Classification