Results 21 to 30 of about 42,568 (290)
Cluster Attack: Query-based Adversarial Attacks on Graph with Graph-Dependent Priors
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022 While deep neural networks have achieved great success in graph analysis, recent work has shown that they are vulnerable to adversarial attacks. Compared with adversarial attacks on image classification, performing adversarial attacks on graphs is more challenging because of the discrete and non-differential nature of the adjacent matrix for a graph ...
Zhengyi Wang +4 more
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Attack Graph Obfuscation [PDF]
, 2017 Before executing an attack, adversaries usually explore the victim's network in an attempt to infer the network topology and identify vulnerabilities in the victim's servers and personal computers. Falsifying the information collected by the adversary post penetration may significantly slower lateral movement and increase the amount of noise generated ...
Hadar Polad, Rami Puzis, Bracha Shapira
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Robust Attack Graph Generation
CoRR, 2022 We present a method to learn automaton models that are more robust to input modifications. It iteratively aligns sequences to a learned model, modifies the sequences to their aligned versions, and re-learns the model. Automaton learning algorithms are typically very good at modeling the frequent behavior of a software system.
Dennis Mouwen, Sicco Verwer, Azqa Nadeem
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Graph matching attack description.
, 2022 Graph matching attack description.
Youzhe Heng (13844549) +3 more
core +1 more source
Portrait Analysis of Threat Intelligence for Attack Recognition [PDF]
Jisuanji gongcheng, 2020 New network attacks are getting more covert and persistent with a high proliferation,resulting in a sudden increase in the difficulty of attack recognition and detection.
YANG Peian, LIU Baoxu, DU Xiangyu
doaj +1 more source
Flowchart of graph matching attack.
, 2022 Flowchart of graph matching attack.
Youzhe Heng (13844549) +3 more
core +1 more source
Graph auto-encoder with a personalized PageRank for model inversion attack on graph neural networks [PDF]
PeerJ Computer ScienceModel inversion attack is the well-known privacy attack, in which the attacker infers the sensitive information of the input data by analyzing the output results of the model.
Ning Luan +6 more
doaj +2 more sources
APT Attack Detection Based on Graph Convolutional Neural Networks
International Journal of Computational Intelligence Systems, 2023 Advanced persistent threat (APT) attacks are malicious and targeted forms of cyberattacks that pose significant challenges to the information security of governments and enterprises.
Weiwu Ren +6 more
doaj +1 more source
An Intelligent Communication Warning Vulnerability Detection Algorithm Based on IoT Technology
IEEE Access, 2019 This paper mainly studies the vulnerability intelligent early warning technology in the IoT environment, and studies the network security assessment method based on the attack graph association analysis of the IoT environment, and analyzes the attack ...
Mao Yi, Xiaohui Xu, Lei Xu
doaj +1 more source
A Survey of Automatic Generation of Attack Trees and Attack Graphs
CoRR, 2023 Graphical security models constitute a well-known, user-friendly way to represent the security of a system. These kinds of models are used by security experts to identify vulnerabilities and assess the security of a system. The manual construction of these models can be tedious, especially for large enterprises.
Alyzia Maria Konsta +3 more
openaire +2 more sources