Noise-Response Analysis of Deep Neural Networks Quantifies Robustness and Fingerprints Structural Malware

31 July 2020

Papers citing "Noise-Response Analysis of Deep Neural Networks Quantifies Robustness and Fingerprints Structural Malware"

6 / 6 papers shown

Title
Persistent Backdoor Attacks in Continual Learning Zhen Guo Abhinav Kumar R. Tourani AAML 27 3 0 20 Sep 2024
How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data Zhiyuan Zhang Lingjuan Lyu Weiqiang Wang Lichao Sun Xu Sun 21 35 0 03 Sep 2021
EX-RAY: Distinguishing Injected Backdoor from Natural Features in Neural Networks by Examining Differential Feature Symmetry Yingqi Liu Guangyu Shen Guanhong Tao Zhenting Wang Shiqing Ma X. Zhang AAML 22 8 0 16 Mar 2021
Baseline Pruning-Based Approach to Trojan Detection in Neural Networks P. Bajcsy Michael Majurski AAML 34 8 0 22 Jan 2021
Blind Backdoors in Deep Learning Models Eugene Bagdasaryan Vitaly Shmatikov AAML FedML SILM 29 298 0 08 May 2020
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems Edward Chou Florian Tramèr Giancarlo Pellegrino AAML 168 287 0 02 Dec 2018