本文介绍图对抗攻击相关的三篇文章:Adversarial Attacks on Neural Networks for Graph Data[1]、 Adversarial Attacks on Graph Neural Networks via Meta Learning[2]和Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective[3]。 一、图对抗攻击 由于深度神经网络强大的表示学习能力,近...
Understanding Universal Adversarial Attack and Defense on Graph Compared with traditional machine learning model, graph neural networks (GNNs) have distinct advantages in processing unstructured data. However, the vulne... T Wang,Z Pan,G Hu,... - 《Int.j.semantic Web Inf.syst》 被引量: 0发表...
This paper introduces the related concepts of existing graph adversarial attack and defense algorithms and analyzes the basic idea and implementation of each algorithm. Moreover, we compare the strategies, target tasks, advantages and disadvantages of typical algorithms. Through the summary of the state...
如果直接对目标节点v0进行修改,则称为直接攻击(direct attack);反之,对v0节点以外的节点进行修改,间接地影响v0的分类结果,称为影响者攻击(influencer attack)。 基于图的对抗性攻击模型可定义为下式(式1),其中 Z∗是GCN分类模型, θ∗ 是根据扰动后的图训练得到的参数, (A′,X′)≈(A,X) 用于确保...
A curated collection of adversarial attack and defense on graph data. - EdisonLeeeee/Graph-Adversarial-Learning
Sun, L., et al.: Adversarial attack and defense on graph data: a survey. In: CoRR abs/1812.10528 (2018).arXiv: 1812.10528 Tang, H., et al.: Adversarial attack on hierarchical graph pooling neural networks. In: arXiv preprintarXiv:2005.11560(2020) ...
We also propose other attack methods with different levels of access to the target classifier in Sec 3.2. We experimentally show the vulnerability of GNN models in Sec 4, and also present a way of doingdefense against such attacks. 2. Background Aset of graphs is denoted by G = {Gi } ...
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attack,而通过对一些不包括v0在内的一个node set(是整个graph的node set的一个子集)进行攻击是influencer attack,也就是间接地通过节点间的相互影响对v0进行攻击。attack的任务可以被写作 也就是攻击的目标在于使得目标节点的预测值和被攻击前的正确预测值之间的差距最大化,还有一点要注意的是预测模型的参数由θ变...
After that, we provide comments and discussions on the effectiveness of the presented attack and defense techniques. The remainder of the paper is organized as follows: In Section 2, we first sketch out the background. In Section 3, we detail several classic adversarial attack methods. In ...