Abstract
Today’s web represents the most extensive engineered system ever created by humankind. Web security is critical to web application providers and end-users. Burp Suite is established as a state-of-the-art and fully featured set of tools for web vulnerability scanners. This paper presents a novel approach using state of the art Machine Learning algorithms applied to the Burp Suite extension. These algorithms were used to scan for: SQL injection, Cross-Site Request Forgery, and XML External Entity vulnerabilities in university web applications. The results show that the best algorithm is Long Short-Term Memory and that the targeted website is safe to use.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
