A New Database Integrity Protection Approach Against SQL Injection Attacks (SQLIAs)

SQL Injection Attacks (SQLIAs) are among the most significant and serious threats to web applications, empowering assailants to employ countless techniques in order to steal and/or tamper data stored in databases, in addition to exploit vulnerabilities and gain unauthorized access. The unauthorized modification of sensitive data could compromise the integrity of the entire database. Therefore, this paper proposes an approach to protect database integrity against SQL injection attacks. The proposed approach uses a structured methodology to identifying the associated vulnerabilities, namely threat modeling and vulnerability analysis, likewise for development and effectiveness evaluation. Moreover, the methodology incorporates Support Vector Machine (SVM), a machine learning algorithm, to enhance the detection and prevention of SQL Injection Attacks (SQLIAs) while ensuring database integrity. Consequently, the proposed method enhances security measures by preventing unauthorized modifications to safeguard data integrity.