Advances in Data Leak Detection: A Review of SQL Injection Detection Techniques and Challenges

Abstract

In the current landscape where important processes are almost entirely dependent on web apps, SQL injection becomes an important issue for information-stealing throughout many organizations worldwide. This paper aims to review that data leak can be detected from a technical perspective of SQL injection including strategies and techniques to minimize related risk. As a first step, as an overview SQL injection and its associates with them consequences, the paper then go further to various important detection methods such as signatures and anomalies-based processes. It is noteworthy that the paper also explores the function of machine learning and artificial intelligence in improving recognition correctness. As we illustrate the effects of SQL injection attacks on various organizations, we will as well simulate the process of drawing the lessons learnt to prevent and combat the attacks. Obstacles and perspectives in the sphere are stated, which will guide a researcher and a practitioner on his way to raise the quality of data leak detecting technologies used across numerous branches of the economy. This article will weaving together the current blackout and will aims at identifying the gaps through which the attackers are able to get access to the system by the means of SQL injection. Keywords— Data leak detection, SQL injection, Web applications, Security, Detection techniques, Machine learning, Anomaly-based detection, Signature-based detection, Prevention, Mitigation.