Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model

Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model

Web applications’ popularity has raised attention in various service domains, which increased the concern about cyber-attacks. One of these most serious and frequent web application attacks is a Cross-site scripting attack (XSS). It causes grievous harm to victims. Existing security methods against...

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Bibliographic Details
Main Authors: Isam Kareem Thajeel, Khairulmizam Samsudin, Shaiful Jahari Hashim, Fazirulhisyam Hashim
Format: Article
Language:English
Published: Elsevier 2023-06-01
Series:Journal of King Saud University: Computer and Information Sciences
Subjects:
Cross-Site Scripting (XSS) Attack
Web Application Security
Feature Drift
Dynamic Feature Selection
Multi-agent Reinforcement Learning
Online Access:http://www.sciencedirect.com/science/article/pii/S1319157823000204

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http://www.sciencedirect.com/science/article/pii/S1319157823000204

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