JStrong: Malicious JavaScript detection based on code semantic representation and graph neural network

Web development technology has experienced significant progress. The creation of JavaScript has highly enriched the interactive ability of the client. However, the attacker uses the dynamic characteristics of the JavaScript language to embed malicious code into web pages to achieve the purpose of sm...

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Veröffentlicht in:	Computers & security Jg. 118; S. 102715
Hauptverfasser:	Fang, Yong, Huang, Chaoyi, Zeng, Minchuan, Zhao, Zhiying, Huang, Cheng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier Ltd 01.07.2022 Elsevier Sequoia S.A
Schlagworte:	Classification Code representation Confusion Dependency Dynamic characteristics Graph neural network Graph neural networks Graph theory Graphical representations Java JavaScript Malicious JavaScript Malware Networks Neural networks Program dependency graph Scripts detection Semantics Smuggling Source code Syntax Websites Malicious JavaScript Scripts detection Program dependency graph Code representation Graph neural network
ISSN:	0167-4048, 1872-6208
Online-Zugang:	Volltext
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