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Future Internet, 2023 The correct and efficient measurement of security properties is key to the deployment of effective cyberspace protection strategies. In this work, we propose GRAPH4, which is a system that combines different security metrics to design an attack detection
Giacomo Gori +5 more
doaj +3 more sources
Survey: Automatic generation of attack trees and attack graphs [PDF]
Computers and SecurityGraphical security models constitute a well-known, user-friendly way to represent the security of a system. These classes 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 +2 more
exaly +2 more sources
An edge sensitivity based gradient attack on graph isomorphic networks for graph classification problems [PDF]
Scientific ReportsGraph Neural Networks have gained popularity over the past few years. Their ability to model relationships between entities of the same and different kind, represent molecules, model flow etc. have made them a go to tool for researchers.
Srinitish Srinivasan +1 more
doaj +2 more sources
A Survey of MulVAL Extensions and Their Attack Scenarios Coverage
IEEE Access, 2023 Organizations employ various adversary models to assess the risk and potential impact of attacks on their networks. A popular method of visually representing cyber risks is the attack graph. Attack graphs represent vulnerabilities and actions an attacker
David Tayouri +3 more
doaj +1 more source
Key path analysis method for large-scale industrial control network
网络与信息安全学报, 2021 In order to solve the problem of high time-consuming and resource-consuming quantitative calculation of large-scale industrial control network attack graphs, a key path analysis method for large-scale industrial control networks was proposed.
ZHANG Yaofang,QU Haikuo, WANG Zibo, WANG Bailing +1 more
doaj +3 more sources
IEEE Access, 2023 Vulnerability assessment in industrial IoT networks is critical due to the evolving nature of the domain and the increasing complexity of security threats.
Omar Saif Musabbeh Bin Hamed Almazrouei +3 more
doaj +1 more source
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
openaire +2 more sources
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
openaire +2 more sources
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
openaire +2 more sources
Transferable Graph Backdoor Attack
Proceedings of the 25th International Symposium on Research in Attacks, Intrusions and Defenses, 2022 Accepted by the 25th International Symposium on Research in Attacks, Intrusions, and ...
Shuiqiao Yang +7 more
openaire +2 more sources