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Apr 13, 2023 · When a deep learning-based model is attacked by backdoor attacks, it behaves normally for clean inputs, whereas outputs unexpected results ...
To address this new threat, in this paper, we propose a new defense mechanism that can detect and mitigate backdoor attacks with dynamic and invisible triggers.
BackdoorBench is a comprehensive benchmark of backdoor learning, which studies the adversarial vulnerablity of deep learning models in the training stage. It ...
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Mar 25, 2024 · In this section, we study the evasiveness of LOTUS against. 4 well-known trigger-inversion based backdoor detection methods, including Neural ...
To ameliorate this issue, we propose a novel backdoor attack on deep ReID under a new all-to- unknown scenario, called Dynamic Triggers Invisible Backdoor.
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In this work, we propose GhostEncoder, the first dynamic invisible backdoor attack on SSL. Unlike existing backdoor attacks on SSL, which use visible or static ...
Backdoor learning is an emerging research area, which discusses the security issues of the training process towards machine learning algorithms.
Oct 13, 2023 · Detecting and Mitigating Backdoor Attacks with Dynamic and Invisible Triggers. Neural Information Processing. Abstract. When a deep learning ...
Nov 20, 2022 · In this paper, we focus on the backdoor attack on deep ReID models. Existing backdoor attack methods follow an all-to-one/all attack scenario, ...
Inspired by the recent advance in DNN-based image steganography, sample-specific invisible additive noises as backdoor triggers are generated by encoding an ...