SQL Injection Attack Detection by Machine Learning Classifier

SQL Injection is one of the top 10 vulnerabilities in web-based systems. This attack essentially penetrates the logical section of the database. If the database has a logical flaw, the attackers send a new type of logical payload and get all of the user's credentials. Despite the fact that technology has advanced significantly in recent years, SQL injections can still be carried out by taking advantage of security flaws. On the Kaggle SQL Injection Dataset, authors used multiple machine learning methods to identify and detect SQL Injection assaults, including Logistic Regression, AdaBoost (Adaptive Boosting), Random Forest, Naive Bayes, and XGBoost (Extreme Gradient Boosting) Classifier. According to this research, the best strategy for detecting SQL inject is Naive Bayes, which has an accuracy of 98.33, which is 2% better than previous work.