Backdoor Detection Through Replicated Execution of Outsourced Training.
Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2025
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD.
Proceedings of the 33rd USENIX Security Symposium, 2024
LLM Dataset Inference: Did you train on my dataset?
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proof-of-Learning is Currently More Broken Than You Think.
Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023
Deep Learning Patch-Based Approach for Hyperspectral Image Classification.
Proceedings of the IEEE International Conference on Electro Information Technology, 2023
On the Fundamental Limits of Formally (Dis)Proving Robustness in Proof-of-Learning.
CoRR, 2022
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning.
Proceedings of the 31st USENIX Security Symposium, 2022
A Zest of LIME: Towards Architecture-Independent Model Distances.
Proceedings of the Tenth International Conference on Learning Representations, 2022
SoK: Machine Learning Governance.
CoRR, 2021
Entangled Watermarks as a Defense against Model Extraction.
Proceedings of the 30th USENIX Security Symposium, 2021
Proof-of-Learning: Definitions and Practice.
Proceedings of the 42nd IEEE Symposium on Security and Privacy, 2021
Proceedings of the 42nd IEEE Symposium on Security and Privacy, 2021
Entangled Watermarks as a Defense against Model Extraction.
CoRR, 2020