Semantic backdoor attacks

Author: hpeb

August undefined, 2024

WebMar 21, 2024 · Unlike classification, semantic segmentation aims to classify every pixel within a given image. In this work, we explore backdoor attacks on segmentation models to misclassify all pixels of a victim class by injecting a specific trigger on non-victim pixels during inferences, which is dubbed Influencer Backdoor Attack (IBA). WebBackdoors 101 — is a PyTorch framework for state-of-the-art backdoor defenses and attacks on deep learning models. It includes real-world datasets, centralized and …

Rethinking the Trigger-injecting Position in Graph Backdoor Attack

WebOn the other hand, in targeted attacks, adversary wants the model to misclassify only a set of chosen samples with minimally affecting its performance on the main task. Such targeted attacks are also known as backdoor attacks. A prominent way of carrying backdoor attacks is through tro-jans (Chen et al. 2024; Liu et al. 2024). A trojan is a care- WebFeb 28, 2024 · The semantic backdoor attack is a type of the backdoor attack where the trigger is a semantic part of the sample; i.e., the trigger exists naturally in the original dataset and the attacker can pick a naturally occurring feature as the backdoor trigger, which causes the model to misclassify even unmodified inputs. brad glazier

BadNL: Backdoor Attacks against NLP Models with Semantic …

WebAug 8, 2024 · There are two different types of Backdoor attacks. They are as listed as follows – 1. Administrative Backdoor Attack: Software developers create backdoor pathways seldom in their program so if by chance any failure is recorded into the computer system then the developers will have access to the code and can help to involve the … WebMar 22, 2024 · Vulnerabilities of Deep Learning-Driven Semantic Communications to Backdoor (Trojan) Attacks March 2024 DOI: 10.1109/CISS56502.2024.10089692 Conference: 2024 57th Annual Conference on... WebThese backdoor attacks are non-semantic backdoor attacks, where the trigger is independent of the benign samples, so the attacker needs to modify samples in the … brad gomel

Figure 1 from Invisible Encoded Backdoor attack on ... - Semantic …

Backdoor Attack with Sample-Specific Triggers Semantic Scholar

WebApr 5, 2024 · Backdoor attacks have been demonstrated as a security threat for machine learning models. Traditional backdoor attacks intend to inject backdoor functionality into … WebPrevious backdoor attacks predominantly focus on computer vision (CV) applications, such as image classification. In this paper, we perform a systematic investigation of backdoor … suzanne vega paul millsWebAbstract Textual backdoor attacks are a kind of practical threat to NLP systems. By injecting a backdoor in the training phase, the adversary could control model predictions via predefined triggers. As various attack and defense models have been proposed, it is of great significance to perform rigorous evaluations. brad glazer

"WebMar 25, 2024 · Backdoor attack aims at inducing neural models to make incorrect predictions for poison data while keeping predictions on the clean dataset unchanged, … " - Semantic backdoor attacks

Rethinking the Trigger-injecting Position in Graph Backdoor Attack

BadNL: Backdoor Attacks against NLP Models with Semantic …

Semantic backdoor attacks

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