ExPLoit: Extracting Private Labels in Split Learning
Sanjay Kariyappa, Moinuddin K Qureshi, "ExPLoit: Extracting Private Labels in Split Learning", IEEE Conference on Secure and Trustworthy Machine Learning, 2023
Publications
Noise-Resilient DNN: Tolerating Noise in PCM-Based AI Accelerators via Noise-Aware Training
Sanjay Kariyappa, Hsinyu Tsai, Katie Spoon, Stefano Ambrogio, Pritish Narayanan, Charles Mackin, An Chen, Moinuddin Qureshi, Geoffrey W Burr, "Noise-Resilient DNN: Tolerating Noise in PCM-Based AI Accelerators via Noise-Aware Training", IEEE Transactions on Electron Devices, 2021
Maze: Data-free model stealing attack using zeroth-order gradient estimation
Sanjay Kariyappa, Atul Prakash, Moinuddin K Qureshi, "Maze: Data-free model stealing attack using zeroth-order gradient estimation", Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021
Enabling Inference Privacy with Adaptive Noise Injection
S Kariyappa, O Dia, MK Qureshi, "Enabling Inference Privacy with Adaptive Noise Injection" arXiv preprint arXiv:2104.02261, 2021
Protecting DNNs from Theft using an Ensemble of Diverse Models
Sanjay Kariyappa, Atul Prakash, Moinuddin K Qureshi, "Protecting DNNs from Theft using an Ensemble of Diverse Models", International Conference on Learning Representations, 2020
Defending against model stealing attacks with adaptive misinformation
Sanjay Kariyappa, Moinuddin K Qureshi, "Defending against model stealing attacks with adaptive misinformation", Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
Reducing the impact of phase-change memory conductance drift on the inference of large-scale hardware neural networks
S Ambrogio, M Gallot, K Spoon, H Tsai, C Mackin, M Wesson, S Kariyappa, P Narayanan, C-C Liu, A Kumar, A Chen, GW Burr, "Reducing the impact of phase-change memory conductance drift on the inference of large-scale hardware neural networks", IEEE International Electron Devices Meeting, 2019