https://semarakilmu.com.my/journals/index.php/sijml <p>The <strong>Semarak International Journal of Machine Learning (SIJML)</strong> is a is a gold open-access, peer reviewed academic journal with the aim to provide an international platform for academic research by publishing original high-quality research and review articles. The journal scope includes but are not limited to data mining, artificial intelligence, natural language processing (NLP), neural networks, software engineering, bioinformatics and their applications in the areas of science and engineering.</p> <h3><strong>EVENTS UPDATE</strong><br /><br /><strong>Semarak International Research Article Competition 2024 III </strong>(SIRAC 2024 III)</h3> <p><a href="https://submit.confbay.com/conf/sirac2024_3"><strong><img src="https://akademiabaru.com/submit/public/site/images/nurulain/sirac-iii.png" alt="" width="931" height="470" /></strong></a></p> <div class="tribe-events-schedule tribe-clearfix">Welcome to our esteemed research article competition! We’re thrilled to invite scholars, researchers, and practitioners worldwide to showcase their groundbreaking [...] <a href="https://submit.confbay.com/conf/sirac2024_3"><strong>READ MORE &gt;&gt;</strong></a></div> Semarak Ilmu Publishing en-US Semarak International Journal of Machine Learning 3030-5241 https://semarakilmu.com.my/journals/index.php/sijml/article/view/13180 <p>SQL Injection is one of the most common vulnerabilities exploited for both privacy breaches and financial damage. It remains the top vulnerability on the most recent OWASP Top 10 list, with the number of such attacks on the rise. The SQL Injection Detection Challenge is addressed using machine learning algorithms. By employing a classification method, communications are identified as either SQL Injection or plain text. This research proposes a machine learning framework to assess the feasibility of using a machine learning classifier to detect SQL Injection attacks. Classification algorithms such as Random Forest, Gradient Boosting, SVM, and ANN are utilized. As a result, ANN demonstrated superior performance and required less time to detect SQL Injection attacks.</p> Laila Aburashed Marah AL Amoush Wardeh Alrefai Copyright (c) 2024 Semarak International Journal of Machine Learning 2024-06-30 2024-06-30 2 1 1 12 10.37934/sijml.2.1.112