Machine and deep learning-based XSS detection approaches: a systematic literature review
Web applications are paramount tools for facilitating services providing in the modern world. Unfortunately, the tremendous growth in the web application usage has resulted in a rise in cyberattacks. Cross-site scripting (XSS) is one of the most frequent cyber security attack vectors that threaten t...
Main Authors: | Thajeel, Isam Kareem, Samsudin, Khairulmizam, Hashim, Shaiful Jahari, Hashim, Fazirulhisyam |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023
|
Online Access: | http://psasir.upm.edu.my/id/eprint/109487/1/1-s2.0-S1319157823001829-main.pdf |
Similar Items
-
Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model
by: Kareem Thajeel, Isam, et al.
Published: (2023) -
Current state of research on cross-site scripting (XSS) – a systematic literature review
by: Hydara, Isatou, et al.
Published: (2015) -
Deep learning approach in DOA estimation: a systematic literature review
by: Ge, Shengguo, et al.
Published: (2021) -
Auditing the XSS defence features implemented in web application programs
by: Shar, Lwin Khin, et al.
Published: (2013) -
Streamlined security framework for defence against XSS attacks targeted at HTML5
by: Cheng, Chi Chung.
Published: (2012)