Reverse Engineering Imperceptible Backdoor Attacks on Deep Neural Networks for Detection and Training Set Cleansing

15 October 2020

Papers citing "Reverse Engineering Imperceptible Backdoor Attacks on Deep Neural Networks for Detection and Training Set Cleansing"

7 / 7 papers shown

Title
Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses M. Ferrag Othmane Friha B. Kantarci Norbert Tihanyi Lucas C. Cordeiro Merouane Debbah Djallel Hamouda Muna Al-Hawawreh K. Choo 25 43 0 17 Jun 2023
Training set cleansing of backdoor poisoning by self-supervised representation learning H. Wang Soroush Karami Ousmane Amadou Dia H. Ritter E. Emamjomeh-Zadeh J. Chen Zhen Xiang D. J. Miller G. Kesidis SSL 23 4 0 19 Oct 2022
Post-Training Detection of Backdoor Attacks for Two-Class and Multi-Attack Scenarios Zhen Xiang David J. Miller G. Kesidis AAML 28 47 0 20 Jan 2022
Backdoor Attack and Defense for Deep Regression Xi Li G. Kesidis David J. Miller V. Lucic AAML 11 6 0 06 Sep 2021
A Backdoor Attack against 3D Point Cloud Classifiers Zhen Xiang David J. Miller Siheng Chen Xi Li G. Kesidis 3DPC AAML 28 76 0 12 Apr 2021
Clean-Label Backdoor Attacks on Video Recognition Models Shihao Zhao Xingjun Ma Xiang Zheng James Bailey Jingjing Chen Yu-Gang Jiang AAML 196 274 0 06 Mar 2020
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems Edward Chou Florian Tramèr Giancarlo Pellegrino AAML 168 287 0 02 Dec 2018