Artificial Intelligence for Web Application Firewall (WAF): A Comprehensive Review

Abstract

The increasing prevalence of cyberattacks that bypass traditional defenses necessitates prioritizing web application security .So, that create an urgent need to use “firewalls”, especially with web applications. The paper submitted a summary of the search and analysis of the scientific literature on web applications, in addition to the studies that have been suggested model for a “web application firewall (WAF)” that employed features engineering and machine learning to identify frequent online threats. The existing research  examined  WAFs and test their effectiveness in identifying fraudulent requests using "machine learning algorithms" like "Naive Bayes", "k-Nearest Neighbors", "Support Vector Machines", and linear regression. The studies integration of AI algorithms with existing WAF has shown achieved accuracy rates ranging from 92% to 99% to be highly effective in mitigating attacks.

Country : Iraq

1 Aya A. Zaki2 Saja J. Mohammed

  1. Department of Computer Science, College of Computer Science and Mathematics, University of Mosul, Mosul, Iraq
  2. Department of Computer Science, College of Computer Science and Mathematics, University of Mosul, Mosul, Iraq

IRJIET, Volume 8, Issue 11, November 2024 pp. 219-224

doi.org/10.47001/IRJIET/2024.811027

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