Manuscript Title:

SQL INJECTION ATTACK DISCOVERY AND COUNTERACTION: SURVEY

Author:

AMMAR A. AHMED, NAJLA B. AL DABBAGH

DOI Number:

DOI:10.17605/OSF.IO/HKPS9

Published : 2023-05-10

About the author(s)

1. AMMAR A. AHMED - Department of Computer science, College of Computer Science and Mathematics, University of Mosul, Mosul, Iraq.
2. NAJLA B. AL DABBAGH - Department of Computer science, College of Computer Science and Mathematics, University of Mosul, Mosul, Iraq.

Full Text : PDF

Abstract

This study analyzed the impact of web applications on society and the economy, while recognizing potential security risks associated with them. It centered explicitly on the SQL injection onslaught, which is a typical endeavor used by programmers to gain unauthorized acceptance of sensitive data through web applications. We note that approval of fake information is a huge component that adds to the inability of web applications to SQL Injection onslaughts. This study talks about various techniques that have been created to identify and thwart such onslaughts. This includes using programming hardware that can recognize SQL Injection vulnerabilities, performing secure encryption exercises, and using network security efforts to prevent unauthorized access. Likewise, the Momentum Path of Exploration is examined here, which shows the need for additional comprehensive methods to handle SQL Injection onslaughts. This study recommended that a combination of preventive measures, including trainings in secure cryptography and high-level security arrangements for the organization, would be important to satisfactorily protect against these kinds of onslaughts.


Keywords

Machine Learning, SQL Injection; Neural Network.