Mudjacking: Patching Backdoor Vulnerabilities in Foundation Models

22 February 2024

Papers citing "Mudjacking: Patching Backdoor Vulnerabilities in Foundation Models"

5 / 5 papers shown

Title
DeBackdoor: A Deductive Framework for Detecting Backdoor Attacks on Deep Models with Limited Data Dorde Popovic Amin Sadeghi Ting Yu Sanjay Chawla Issa M. Khalil AAML 49 0 0 27 Mar 2025
Poison Forensics: Traceback of Data Poisoning Attacks in Neural Networks Shawn Shan A. Bhagoji Haitao Zheng Ben Y. Zhao AAML 86 50 0 13 Oct 2021
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 267 3,369 0 09 Mar 2020
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems Edward Chou Florian Tramèr Giancarlo Pellegrino AAML 168 287 0 02 Dec 2018
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,194 0 01 Sep 2014