Detection of payload injection in Firewall Using Machine Learning
K Surendhar, Bishwajeet Kumar Pandey, G Geetha, Hardik Gohel
Abstract
The modern web application processes a huge amount of data to deliver customized services to the users, lack of security makes this application to becomes a victim of cyberattacks. The injection attacks line SQLI and XSS are the attacks that commonly take place. The firewall is implemented in the various layers of the OSI model to provide security for the assets. Each layer firewall uses different techniques and provides the functionality to prevent the attack. One of the important firewall designs is the Application layers firewall, which is also known as the web application firewall WAF, which is used to examine the external request, and protocols to prevent the application layer attacks such as SQLI and XSS. The XSS is a critical vulnerability of web applications. With the XSS the attacker can Steal confidential information in an unauthorized way. With the XSS attack, the attacker set up phishing sites on the websites. In this paper, we are discussing how the application layer firewall is detecting the malicious request patterns of the payloads using the application of machine learning algorithms. Keywords- Supervision, Firewall, XSS, Machine learning, SQLI