An Improved Approach for SQL Injection Vulnerabilities Detection

Abstract

The attack of SQL injection is a well-known threat to web applications, which leads to great damages of confidentiality and integrity of information in databases. Therefore, it is essential for each web applications to detect SQL injection vulnerabilities and eliminate the hidden danger. In this paper, an approach based on penetration testing named YUKIER is proposed to achieve higher effectiveness and preciseness on identifying security vulnerabilities. We compare YUKIER with SQLiX and Paros Proxy, and the experiment results demonstrate that our proposed approach has the higher performances with respect to the existing circumstance.

SQL Injection Vulnerability Detection Using Deep Learning: A Feature-based Approach

“…The papers [24][25][26][27][28][29][30][31][32] use pattern matching approaches to detect and prevent SQLi attacks. These operations are performed at the runtime, which makes these practices time-consuming and complex.…”

“…Thereafter, it is checked if the request is for an SQLi attack or not. C. Shi et al [26] proposed a self-learning SQLi detection approach with a pattern  ISSN: 2089-3272 IJEEI, Vol. 9, No.…”

“…There are numerous SQLi detection approaches to diminish such attacks through SQLi vulnerability exploitation. These detection approaches can be of various types: detection using pattern matching [24][25][26][27][28][29][30][31][32], learning-based detection [33][34][35][36][37][38][39][40][41][42][43], and other approaches [44][45][46][47][48][49].…”