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...
Saved in:
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 http://psasir.upm.edu.my/id/eprint/109487/ https://linkinghub.elsevier.com/retrieve/pii/S1319157823001829 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
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) -
A taxonomy study of XSS Vulnerabilities
by: Nayeem, Khan, et al.
Published: (2017) -
An improved LSTM-PCA ensemble classifier for SQL injection and XSS attack detection
by: Stiawan, Deris, et al.
Published: (2023) -
Network intrusion detection system: A systematic study of machine learning and deep learning approaches
by: Zeeshan, Ahmad, et al.
Published: (2020)