Don't Trigger Me! A Triggerless Backdoor Attack Against Deep Neural
Networks

Don't Trigger Me! A Triggerless Backdoor Attack Against Deep Neural Networks

7 October 2020

Michael Backes

Papers citing "Don't Trigger Me! A Triggerless Backdoor Attack Against Deep Neural Networks"

9 / 9 papers shown

Title
The Ripple Effect: On Unforeseen Complications of Backdoor Attacks Rui Zhang Yun Shen Hongwei Li Wenbo Jiang Hanxiao Chen Yuan Zhang Guowen Xu Yang Zhang SILM AAML 32 0 0 16 May 2025
A Backdoor Attack Scheme with Invisible Triggers Based on Model Architecture Modification Yuan Ma Xu Ma Jiankang Wei Jinmeng Tang Xiaoyu Zhang Yilun Lyu Kehao Chen Jingtong Huang 93 0 0 22 Dec 2024
Sample-Independent Federated Learning Backdoor Attack in Speaker Recognition Weida Xu Yang Xu Sicong Zhang FedML AAML 44 0 0 25 Aug 2024
SoK: A Systematic Evaluation of Backdoor Trigger Characteristics in Image Classification Gorka Abad Jing Xu Stefanos Koffas Behrad Tajalli S. Picek Mauro Conti AAML 67 5 0 03 Feb 2023
Backdoor Attacks on Crowd Counting Yuhua Sun Tailai Zhang Xingjun Ma Pan Zhou Jian Lou Zichuan Xu Xing Di Yu Cheng Lichao AAML 19 15 0 12 Jul 2022
Accumulative Poisoning Attacks on Real-time Data Tianyu Pang Xiao Yang Yinpeng Dong Hang Su Jun Zhu 37 20 0 18 Jun 2021
Hidden Backdoors in Human-Centric Language Models Shaofeng Li Hui Liu Tian Dong Benjamin Zi Hao Zhao Minhui Xue Haojin Zhu Jialiang Lu SILM 40 147 0 01 May 2021
Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks Avi Schwarzschild Micah Goldblum Arjun Gupta John P. Dickerson Tom Goldstein AAML TDI 21 162 0 22 Jun 2020
Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges Rob Ashmore R. Calinescu Colin Paterson AI4TS 34 116 0 10 May 2019