JAVA']JAVASCRIPT MALWARE DETECTION USING A HIGH-LEVEL FUZZY PETRI NET

被引：0

作者：

Shen, Victor R. L. ^{[1
]}

Wei, Chin-Shan ^{[1
]}

Juang, Tony Tong-Ying ^{[1
]}

机构：

[1] Natl Taipei Univ, Dept Comp Sci & Informat Engn, Taipei, Taiwan

来源：

PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOL 2 | 2018年

关键词：

Cyber security; !text type='Java']Java[!/text]Script; Mal ware detection. High-level fuzzy Petri net;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

JavaScript is a scripting language for web pages that allows website creators to run any code they want when users visit their website. Therefore, malicious JavaScript is the greatest threats within the cyber world. This paper proposes a novel method of detecting the JavaScript malware by using a high-level fuzzy Petri net (HLFPN). Firstly, the web pages are crawled to get JavaScript files. Secondly, the malicious features are extracted from JavaScript code. Finally, an HLFPN is used to determine the malicious code. The experimental results can support the effectiveness of our approach.

引用

页码：511 / 514

页数：4

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