AdvDoor: Adversarial Backdoor Attack of Deep Learning System (ISSTA 2021) 一、简介本文提出的算法是基于数据投毒的后门攻击,主要有以下特点: 1.不同于常见的patch backdoor,本文采用的是adversarial backd…
Digital Attack:指对抗性扰动被标记在数字输入上,例如通过修改数字图像中的像素; Physical Attack:指对物理世界中的攻击对象做出对抗性扰动,不过对于系统捕获的digital input是不可控的,可以理解为在现实世界中发动攻击。 评价指标 后门攻击的成功通常可以通过干净数据准确率(Clean Data Accuracy, CDA)和攻击成功率(Attack...
backdoor attack and defense总结 :Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review 目录 简介 对比 定性分析 攻击方式攻击分类 攻击...adversarial attack(对抗攻击),它的目标是生成能够使模型误分类的adversarial sample(对抗样本),它与backdoor attack的一个重要区别在于,它的攻击阶段...
1. (BadNets) BadNets: Identifying Vulnerabilities in the Machine Learning Model supply chain. Tianyu Gu, Brendan Dolan-Gavitt, Siddharth Garg. 2017. 2. (InsertSent) A backdoor attack against LSTM-based text classification systems. Jiazhu Dai, Chuanshuai Chen. 2019. 3. (SynBkd) Hidden Killer:...
Extensive evaluations across four data sets and the corresponding DNNs demonstrate the state-of-the-art (SOTA) defense performance of EVE compared with five baselines. In particular, EVE under 40% of malicious clients can reduce the attack success rate from 99% to 1%. In addition, we verify ...
近期在读一些关于backdoor(Trojan) attack in deep neural networks(DNN)相关的论文,读着读着就容易忘记论文的内容,所以需要写些东西记录下来,接下来会写一系列有关backdoor attack and defense的文章, 因为博主也是初学者,所以有很多理解不到位的地方,请多多包涵。极力推荐阅读这篇综述,很好地总结了最近几年该领域...
Recent studies have shown that deep neural networks (DNN) are vulnerable to various adversarial attacks. In particular, an adversary can inject a stealthy backdoor into a model such that the compromised model will behave normally without the presence of the trigger. Techniques for generating backdoo...
Graph convolutional networks (GCNs) have been very effective in addressing the issue of various graph-structured related tasks, such as node classification and graph classification. However, recent research has shown that GCNs are vulnerable to a new type of threat called a backdoor attack, where ...
Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective (ICLR 2023) [paper] [code] Provable Robustness against Wasserstein Distribution Shifts via Input Randomization (ICLR 2023) [paper] Don’t forget the nullspace! Nullspace occupancy as a mechanism for out of distributio...
Empirically prove that a triggering pattern based on universal adversarial perturbations is harder to be detected by the SoA defences. Category: reduce trigger visibility, poisoned label, control dataset and label, blackbox 8. Backdoor attack in the physical world Paper Authors: Yiming Li, Tongqin...