GraphXSS: An efficient XSS payload detection approach based on graph convolutional network-Reference-Cited by-同舟云学术

GraphXSS: An efficient XSS payload detection approach based on graph convolutional network

Published:2022-03 Issue: Volume:114 Page:102597
ISSN:0167-4048
Container-title:Computers & Security
language:en
Short-container-title:Computers & Security

Author:

Liu Zhonglin,Fang Yong,Huang Cheng,Han Jiaxuan

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Law,General Computer Science

Reference33 articles.

1. A comparison of machine learning algorithms for detecting XSS attacks;Chen,2019

2. Cluley G.. Cross-platform Boonana Trojan targets facebook users. 2020. Available at https://nakedsecurity.sophos.com/2010/10/28/cross-platform-worm-targets-facebook-users/. Accessed 22, October.

3. Constantin L.. New chinese social networking worm discoverd. 2020. Available at http://news.softpedia.com/news/New-Chinese-Social-Networking-Worm-Discovered-120021.shtml. Accessed 22, October.

4. NLTK: the natural language toolkit;Edward,2002

5. DeepXSS: cross site scripting detection based on deep learning;Fang,2018

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