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Towards Stable and Efficient Training of Verifiably Robust Neural Networks., , , , , and . CoRR, (2019)Spatially Transformed Adversarial Examples., , , , , and . ICLR (Poster), OpenReview.net, (2018)Generating Adversarial Examples with Adversarial Networks., , , , , and . IJCAI, page 3905-3911. ijcai.org, (2018)A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems., , , , and . CoRR, (2024)Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions., , , , , and . CoRR, (2022)A Learning-based Declarative Privacy-Preserving Framework for Federated Data Management., , , , , , , , , and 1 other author(s). CoRR, (2024)Can Shape Structure Features Improve Model Robustness under Diverse Adversarial Settings?, , , , , , and . ICCV, page 7506-7515. IEEE, (2021)Improving Robustness of ML Classifiers against Realizable Evasion Attacks Using Conserved Features., , , , , and . USENIX Security Symposium, page 285-302. USENIX Association, (2019)SMACK: Semantically Meaningful Adversarial Audio Attack., , , and . USENIX Security Symposium, page 3799-3816. USENIX Association, (2023)DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local Smoothing., , , , and . USENIX Security Symposium, page 4787-4804. USENIX Association, (2023)