AN ENHANCED SQL INJECTION DETECTION USING ENSEMBLE METHOD - Doni Putra Purbawa; Azzam Jihad Ulhaq; Gusna Ikhsan; Ary Mazharuddin Shiddiqi (Department of Informatics, Institut Teknologi Sepuluh Nopember, 2023)
SQL injection is a cybercrime that attacks websites. This issue is still a challenging issue in the realm of security that must be resolved. These attacks are very costly financially, which count millions of dollars each year. Due to large data leaks, the losses also impact the world economy, which averages nearly 50 per year, and most of them are caused by SQL injection. In a study of 300,000 attacks worldwide in any given month, 24.6% were SQL injection. Therefore, implementing a strategy to protect against web application attacks is essential and not easy because we have to protect user privacy and enterprise data. This study proposes an enhanced SQL injection detection using the voting classifier method based on several machine learning algorithms. The proposed classifier could achieve the highest accuracy from this research in 97.07%.