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Downstream-agnostic Adversarial Examples., , , , , , and . ICCV, page 4322-4332. IEEE, (2023)SecHOG: Privacy-Preserving Outsourcing Computation of Histogram of Oriented Gradients in the Cloud., , , , and . AsiaCCS, page 257-268. ACM, (2016)Towards Privacy-Preserving Neural Architecture Search., , , , and . ISCC, page 1-6. IEEE, (2022)Challenges and Approaches for Mitigating Byzantine Attacks in Federated Learning., , , , and . TrustCom, page 139-146. IEEE, (2022)PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models against Adversarial Examples., , , , , , , and . AAAI, page 872-880. AAAI Press, (2023)Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks., , , , , , and . AAAI, page 6404-6412. AAAI Press, (2024)Shielding Federated Learning: A New Attack Approach and Its Defense., , , , and . WCNC, page 1-7. IEEE, (2021)Secure Surfing: Privacy-Preserving Speeded-Up Robust Feature Extractor., , , and . ICDCS, page 700-710. IEEE Computer Society, (2016)Depriving the Survival Space of Adversaries Against Poisoned Gradients in Federated Learning., , , , , , and . IEEE Trans. Inf. Forensics Secur., (2024)Variational Bayes for Federated Continual Learning., , , , , , and . CoRR, (2024)