Machine Learning for SQL injection prevention on server-side scripting

SQL injection is the most common web application vulnerability. The vulnerability can be generated unintentionally by software developer during the development phase. To ensure that all secure coding practices are adopted to prevent the vulnerability. The framework of SQL injection prevention using compiler platform and machine learning is proposed. The machine learning part will be described primarily since it is the core of this framework to support SQL injection prediction by conducting 1,100 datasets of vulnerabilities to train machine learning model. The results indicated that decision tree is the best model in term of processing time, highest efficiency in prediction.