A Systematic Literature Review on Detection, Prevention and Classification with Machine Learning Approach

Abstract

When it comes to web application, confidentiality, availability and integrity of individuals and organizations data are not assured. Open Web Application Security Project (OWASP) has identified SQL injection attacks as common threat to the web application. Consequently, many researchers have proposed different approaches for either detection, prevention or classification/categorization of SQL injection attack. Machine learning approach is one of the approaches existing in the literature, though not very much research outputs with this approach are available in the literature. This implies that, future researchers can still apply machine learning approach in addressing SQL injection attack problem. For this reason, this study presents a systematic literature review on SQL injection attack detection, prevention and classification based on machine learning approach. In order to obtain SQL injection attack related articles, various search engines and scholar databases were visited. The authors review analysis revealed that most of the proposed machine leaning approaches were proposed to only detect whether an application is vulnerable to SQL injection attack or not. Very few were proposed to prevent and classify the injection based on the attack type. It is our hope that this review will provide a theoretical background for future research and enable future researches to identify how and where machine learning approaches have been used to address SQL injection attack.