Guarding Machine Learning Hardware Against Physical Side-Channel Attacks

1 September 2021

Papers citing "Guarding Machine Learning Hardware Against Physical Side-Channel Attacks"

8 / 8 papers shown

Title
Stochastic Training for Side-Channel Resilient AI Anuj Dubey Aydin Aysu AAML 14 0 0 07 Jun 2025
MACPruning: Dynamic Operation Pruning to Mitigate Side-Channel DNN Model Extraction Ruyi Ding Cheng Gongye Davis Ranney A. A. Ding Yunsi Fei AAML 112 0 0 24 Feb 2025
Defense against ML-based Power Side-channel Attacks on DNN Accelerators with Adversarial Attacks Xiaobei Yan Chip Hong Chang Tianwei Zhang AAML 72 1 0 07 Dec 2023
BlackJack: Secure machine learning on IoT devices through hardware-based shuffling Karthik Ganesan Michal Fishkin Ourong Lin Natalie Enright Jerger 82 4 0 26 Oct 2023
A Desynchronization-Based Countermeasure Against Side-Channel Analysis of Neural Networks J. Breier Dirmanto Jap Xiaolu Hou S. Bhasin AAML 72 8 0 25 Mar 2023
Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems Shail Dave Alberto Marchisio Muhammad Abdullah Hanif Amira Guesmi Aviral Shrivastava Ihsen Alouani Mohamed Bennai 75 14 0 18 Apr 2022
Cryptanalytic Extraction of Neural Network Models Nicholas Carlini Matthew Jagielski Ilya Mironov FedML MLAU MIACV AAML 168 137 0 10 Mar 2020
MaskedNet: The First Hardware Inference Engine Aiming Power Side-Channel Protection Anuj Dubey Rosario Cammarota Aydin Aysu AAML 88 80 0 29 Oct 2019