Data-efficient backdoor attacks
WebNov 9, 2024 · Recent work has shown that this type of attack, called a poisoning attack, allows adversaries to insert backdoors or trojans into the model, enabling malicious behavior with simple external backdoor triggers at inference time and only a blackbox perspective of the model itself. WebData-Efficient Backdoor Attacks Pengfei Xia, Ziqiang Li, Wei Zhang and Bin Li University of Science and Technology of China, Hefei, China …
Data-efficient backdoor attacks
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WebThe experimental results on CIFAR-10 and ImageNet-10 indicate that the proposed method is effective: the same attack success rate can be achieved with only 47% to 75% of the … WebFeb 13, 2024 · More precisely, backdoor triggers in neuromorphic data can change their position and color, allowing a larger range of possibilities than common triggers in, e.g., the image domain. We propose different attacks achieving up to 100\% attack success rate without noticeable clean accuracy degradation.
WebData-efficient Large Scale Place Recognition with Graded Similarity Supervision Maria Leyva-Vallina · Nicola Strisciuglio · Nicolai Petkov ... Progressive Backdoor Erasing via … WebSep 12, 2024 · Current backdoor attacks rely on generating triggers in the image/pixel domain; however, as we show in this paper, it is not the only domain to exploit and one should always "check the other doors". In this work, we propose a complete pipeline for generating a dynamic, efficient, and invisible backdoor attack in the frequency domain.
WebJan 7, 2024 · Deep neural network (DNNs) provide excellent performance in image recognition, speech recognition, video recognition, and pattern analysis. However, DNNs are vulnerable to backdoor attacks. A backdoor attack allows a DNN to correctly recognize normal data that do not contain a specific trigger but induces it to incorrectly recognize … WebJul 1, 2024 · The data-efficient backdoor attack [203] controlled the choice of which samples to poison according to a filtering-and-updating strategy, which showed improved attack performance compared...
WebJun 10, 2024 · To solve these problems, we propose a two-phase and image-specific triggers generation method to enhance clean-label backdoor attacks. Our methods are (1) powerful: our triggers can both promote the two phases (i.e., the backdoor implantation and activation phase) in backdoor attacks simultaneously; (2) stealthy: our triggers are …
WebFeb 19, 2024 · We propose an efficient target/victim pairs identification approach for backdoor detection based on static weight analysis. It is agnostic to model structures and trigger types and thus can significantly improve the efficiency of backdoor detection for local patch attacks and global transformation attacks. tammy gillis marriedWebDataset distillation has emerged as a prominent technique to improve data efficiency when training machine learning models. It encapsulates the knowledge from a large dataset into a smaller synthetic dataset. ... This study performs the first backdoor attack against the models trained on the data distilled by dataset distillation models in the ... tammy gheeWebFeb 10, 2024 · Empirical evaluation shows that NAIVEATTACK achieves decent attack success rate (ASR) scores in some cases, while DOORPING reaches higher ASR scores (close to 1.0) in all cases. Furthermore, we conduct a comprehensive ablation study to analyze the factors that may affect the attack performance. tyac-f5-m30WebMar 21, 2024 · Backdoor attack is a malicious entry into a system. Learn the meaning, examples and ways to prevent a virus, malware or trojan from hacking your system ... Analytics cookies allow us to analyse our performance to offer you a better online experience and evaluate the efficiency of our campaigns. Personalisation cookies give … tyac eventsWebAccording to the Malwarebytes Labs State of Malware report, backdoors were the fourth most common threat detection in 2024 for both consumers and businesses—respective increases of 34 and 173 percent over the previous year. tammy gilmore brownWebMar 25, 2024 · Backdoor attack [8, 20, 24,31,46] is a training time attack and has emerged as a major security threat to deep neural networks (DNNs) in many application areas (e.g., natural language... tyachevtammy glassburn lancaster oh