Characterizing and Optimizing End-to-End Systems for Private Inference
Karthik Garimella, Zahra Ghodsi, Nandan Kumar Jha, Siddharth Garg, Brandon Reagen
Arxiv preprint
zPROBE: Zero Peek Robustness Checks for Federated Learning
Zahra Ghodsi, Mojan Javaheripi, Nojan Sheybani, Xinqiao Zhang, Ke Huang, Farinaz Koushanfar
Arxiv preprint
CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale
Karthik Garimella, Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen
Arxiv preprint
Sphynx: ReLU-Efficient Network Design for Private Inference
Minsu Cho, Zahra Ghodsi, Brandon Reagen, Siddharth Garg, Chinmay Hegde
IEEE Security and Privacy, 2022.
Circa: Stochastic ReLUs for Private Deep Learning
Zahra Ghodsi, Nandan Kumar Jha, Brandon Reagen, Siddharth Garg
Advances in Neural Information Processing Systems (NeurIPS), Dec 2021
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles
Zahra Ghodsi, Siva Kumar Sastry Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Stephen Keckler, Siddharth Garg, Anima Anandkumar
IEEE Intelligent Vehicles Symposium (IV), Jul 2021
DeepReDuce: ReLU Reduction for Fast Private Inference
Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen
International Conference on Machine Learning (ICML), Jul 2021
CryptoNAS: Private Inference on a ReLU Budget
Zahra Ghodsi, Akshaj Veldanda, Brandon Reagen, Siddharth Garg
Advances in Neural Information Processing Systems (NeurIPS), Dec 2020
[code]
SafeTPU: A Verifiably Secure Hardware Accelerator for Deep Neural Networks
Maria I. Mera Collantes, Zahra Ghodsi, Siddharth Garg
IEEE VLSI Test Symposium (VTS), May 2020
Enabling Timing Error Resilience for Low-Power Systolic-Array Based Deep Learning Accelerators
Jeff Zhang, Zahra Ghodsi, Siddharth Garg, Kartheek Rangineni
IEEE Design & Test, Oct 2019
Outsourcing Private Machine Learning via Lightweight Secure Arithmetic Computation
Siddharth Garg, Zahra Ghodsi, Carmit Hazay, Yuval Ishai, Antonio Marcedone, Muthuramakrishnan Venkitasubramaniam
NeurIPS Workshop on Privacy Preserving Machine Learning (PPML), Dec 2018
Thundervolt: Enabling Aggressive Voltage Underscaling and Timing Error Resilience for Energy Efficient Deep Learning Accelerators
Jeff Zhang, Kartheek Rangineni, Zahra Ghodsi, Siddharth Garg
Design Automation Conference (DAC), June 2018
Safetynets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud
Zahra Ghodsi, Tianyu Gu, Siddharth Garg
Advances in Neural Information Processing Systems (NeurIPS), Dec 2017
[video]
[code]
Optimal Checkpointing for Secure Intermittently-powered IoT Devices
Zahra Ghodsi, Siddharth Garg, Ramesh Karri
IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Nov 2017