Physical Side-Channel Attacks on Embedded Neural Networks: A Survey

21 October 2021

Papers citing "Physical Side-Channel Attacks on Embedded Neural Networks: A Survey"

7 / 7 papers shown

Title
P2W: From Power Traces to Weights Matrix -- An Unconventional Transfer Learning Approach Roozbeh Siyadatzadeh Fatemeh Mehrafrooz Nele Mentens Todor Stefanov 36 0 0 24 Feb 2025
SoK: A Systems Perspective on Compound AI Threats and Countermeasures Sarbartha Banerjee Prateek Sahu Mulong Luo Anjo Vahldiek-Oberwagner N. Yadwadkar Mohit Tiwari AAML 74 0 0 20 Nov 2024
Side-Channel Analysis of OpenVINO-based Neural Network Models Dirmanto Jap J. Breier Zdenko Lehocký S. Bhasin Xiaolu Hou FedML 31 2 0 23 Jul 2024
A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly Yifan Yao Jinhao Duan Kaidi Xu Yuanfang Cai Eric Sun Yue Zhang PILM ELM 34 475 0 04 Dec 2023
DNN-Alias: Deep Neural Network Protection Against Side-Channel Attacks via Layer Balancing Mahya Morid Ahmadi Lilas Alrahis Ozgur Sinanoglu Muhammad Shafique AAML 28 7 0 12 Mar 2023
A Practical Introduction to Side-Channel Extraction of Deep Neural Network Parameters Raphael Joud Pierre-Alain Moëllic S. Pontié J. Rigaud AAML MIACV MLAU 21 13 0 10 Nov 2022
A Review of Confidentiality Threats Against Embedded Neural Network Models Raphael Joud Pierre-Alain Moëllic Rémi Bernhard J. Rigaud 28 6 0 04 May 2021