SQL injection detection and exploitation framework for penetration testing

SQL injection is one of the complex and threatening attack used against SQL database servers and web applications. Attackers use SQL injection to get unauthorized access and perform unauthorized data modification. To mitigate the devastating problem of SQL injection attack, there are many existing t...

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Bibliographic Details
Main Author: Kazmi, Muhammad Ali Naqi
Format: Thesis
Language:English
Published: 2019
Subjects:
Online Access:https://repository.londonmet.ac.uk/7345/1/Kazmi-Muhammad_Final-Thesis.pdf
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author Kazmi, Muhammad Ali Naqi
author_facet Kazmi, Muhammad Ali Naqi
author_sort Kazmi, Muhammad Ali Naqi
collection LMU
description SQL injection is one of the complex and threatening attack used against SQL database servers and web applications. Attackers use SQL injection to get unauthorized access and perform unauthorized data modification. To mitigate the devastating problem of SQL injection attack, there are many existing tools and methods for detection and prevention. Due to the rapid SQL injection growth in recent years, the SQL injection security approaches have been experiencing a paradigm shift from the strenuous manual analysis, signature-based approach to a data-driven, machine learning-based dynamic approach. This research has provided a comprehensive analysis of SQL injection and literature review of the existing SQL injection security methods. The thesis presents a novel semi-automated SQL injection detection and exploitation (IDE) solution using constructive method by combining machine learning and advance Python computation.
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spelling oai:repository.londonmet.ac.uk:73452022-03-31T14:05:15Z https://repository.londonmet.ac.uk/7345/ SQL injection detection and exploitation framework for penetration testing Kazmi, Muhammad Ali Naqi 000 Computer science, information & general works SQL injection is one of the complex and threatening attack used against SQL database servers and web applications. Attackers use SQL injection to get unauthorized access and perform unauthorized data modification. To mitigate the devastating problem of SQL injection attack, there are many existing tools and methods for detection and prevention. Due to the rapid SQL injection growth in recent years, the SQL injection security approaches have been experiencing a paradigm shift from the strenuous manual analysis, signature-based approach to a data-driven, machine learning-based dynamic approach. This research has provided a comprehensive analysis of SQL injection and literature review of the existing SQL injection security methods. The thesis presents a novel semi-automated SQL injection detection and exploitation (IDE) solution using constructive method by combining machine learning and advance Python computation. 2019-05 Thesis NonPeerReviewed text en https://repository.londonmet.ac.uk/7345/1/Kazmi-Muhammad_Final-Thesis.pdf Kazmi, Muhammad Ali Naqi (2019) SQL injection detection and exploitation framework for penetration testing. Doctoral thesis, London Metropolitan University.
spellingShingle 000 Computer science, information & general works
Kazmi, Muhammad Ali Naqi
SQL injection detection and exploitation framework for penetration testing
title SQL injection detection and exploitation framework for penetration testing
title_full SQL injection detection and exploitation framework for penetration testing
title_fullStr SQL injection detection and exploitation framework for penetration testing
title_full_unstemmed SQL injection detection and exploitation framework for penetration testing
title_short SQL injection detection and exploitation framework for penetration testing
title_sort sql injection detection and exploitation framework for penetration testing
topic 000 Computer science, information & general works
url https://repository.londonmet.ac.uk/7345/1/Kazmi-Muhammad_Final-Thesis.pdf
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