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Home > Archives > Volume 20, No 8 (2022) > Article

DOI: 10.14704/nq.2022.20.8.NQ44797

SQL Injection Attacks(SQLIA) detection and prevention methods using machine learning and traditional approach (A Comparison study)

Fouad Raheem Abdulhamza, Dr. Rana JumaaSurayh Al-Janabi

Abstract

This sort of intrusive attack on web-based applications is particularly serious since it might expose the secrets and safety of data. Illegal individuals get access to the web-based database and the data it contains by stealing it. There are a variety of ways to detect and prevent this form of attack, but they are not sufficient since many of them do not work for all types of assaults. In this research, many types of SQL Injection attacks were examined as existing methods of detecting and preventing them. Because of the current techniques of preventing From the user end. The research Comparison used machine learning and the traditional approach to detecting and preventing them and developers would have to create separate validation methods for every web page that obtained data from the server.

Keywords

SQLI, WA, machine learning, traditional approach, detection, prevention

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