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Taxonomy of SQL Injection: ML Trends & Open Challenges

SQL injections are a significant and ever-present threat to web applications and database security. During these attacks, malicious SQL statements are injected into input fields of data-driven systems, leading to unauthorized access and data breaches. Consequently, a need is generated to understand...

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Main Authors: Abobakr Busaeed, Raed Abdullah, Wan Isni Sofiah, Wan Din, Waseem, Quadri, Azlee, Zabidi
Format: Conference or Workshop Item
Language:English
English
Published: IEEE 2023
Subjects:
QA75 Electronic computers. Computer science
T Technology (General)
Online Access:http://umpir.ump.edu.my/id/eprint/38717/1/Taxonomy_of_SQL_Injection_ML_Trends_amp_Open_Challenges.pdf
http://umpir.ump.edu.my/id/eprint/38717/2/Taxonomy%20of%20SQL%20Injection.pdf
http://umpir.ump.edu.my/id/eprint/38717/
https://doi.org/10.1109/ICSECS58457.2023.10256276
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spelling my.ump.umpir.387172023-09-29T13:35:38Z http://umpir.ump.edu.my/id/eprint/38717/ Taxonomy of SQL Injection: ML Trends & Open Challenges Abobakr Busaeed, Raed Abdullah Wan Isni Sofiah, Wan Din Waseem, Quadri Azlee, Zabidi QA75 Electronic computers. Computer science T Technology (General) SQL injections are a significant and ever-present threat to web applications and database security. During these attacks, malicious SQL statements are injected into input fields of data-driven systems, leading to unauthorized access and data breaches. Consequently, a need is generated to understand the nature of the attacks, detection, and effective prevention techniques. This research paper focuses on providing a taxonomy and comprehensive survey of SQL injection attacks, detection, and prevention, including their various types and techniques. Additionally, it explores the current state-of-the-art and evaluation for attacks, detection, and prevention techniques. This research paper also discusses and provides a taxonomy of current machine learning (ML) trends (Taxonomy) and their open challenges for detection purposes. Finally, this paper ends with a discussion aiming to equip system administrators, researchers, scientists and practitioners with the knowledge and strategies to mitigate the risks associated with SQL injection attacks effectively. Eventually, this will help to enhance the security and resilience of web applications and databases in the face of this significant threat. IEEE 2023 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/38717/1/Taxonomy_of_SQL_Injection_ML_Trends_amp_Open_Challenges.pdf pdf en http://umpir.ump.edu.my/id/eprint/38717/2/Taxonomy%20of%20SQL%20Injection.pdf Abobakr Busaeed, Raed Abdullah and Wan Isni Sofiah, Wan Din and Waseem, Quadri and Azlee, Zabidi (2023) Taxonomy of SQL Injection: ML Trends & Open Challenges. In: 2023 IEEE 8th International Conference On Software Engineering and Computer Systems (ICSECS), 25-27 August 2023 , Penang, Malaysia. pp. 382-387.. ISBN 979-8-3503-1094-8 https://doi.org/10.1109/ICSECS58457.2023.10256276
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic QA75 Electronic computers. Computer science
T Technology (General)
spellingShingle QA75 Electronic computers. Computer science
T Technology (General)
Abobakr Busaeed, Raed Abdullah
Wan Isni Sofiah, Wan Din
Waseem, Quadri
Azlee, Zabidi
Taxonomy of SQL Injection: ML Trends & Open Challenges
description SQL injections are a significant and ever-present threat to web applications and database security. During these attacks, malicious SQL statements are injected into input fields of data-driven systems, leading to unauthorized access and data breaches. Consequently, a need is generated to understand the nature of the attacks, detection, and effective prevention techniques. This research paper focuses on providing a taxonomy and comprehensive survey of SQL injection attacks, detection, and prevention, including their various types and techniques. Additionally, it explores the current state-of-the-art and evaluation for attacks, detection, and prevention techniques. This research paper also discusses and provides a taxonomy of current machine learning (ML) trends (Taxonomy) and their open challenges for detection purposes. Finally, this paper ends with a discussion aiming to equip system administrators, researchers, scientists and practitioners with the knowledge and strategies to mitigate the risks associated with SQL injection attacks effectively. Eventually, this will help to enhance the security and resilience of web applications and databases in the face of this significant threat.
format Conference or Workshop Item
author Abobakr Busaeed, Raed Abdullah
Wan Isni Sofiah, Wan Din
Waseem, Quadri
Azlee, Zabidi
author_facet Abobakr Busaeed, Raed Abdullah
Wan Isni Sofiah, Wan Din
Waseem, Quadri
Azlee, Zabidi
author_sort Abobakr Busaeed, Raed Abdullah
title Taxonomy of SQL Injection: ML Trends & Open Challenges
title_short Taxonomy of SQL Injection: ML Trends & Open Challenges
title_full Taxonomy of SQL Injection: ML Trends & Open Challenges
title_fullStr Taxonomy of SQL Injection: ML Trends & Open Challenges
title_full_unstemmed Taxonomy of SQL Injection: ML Trends & Open Challenges
title_sort taxonomy of sql injection: ml trends & open challenges
publisher IEEE
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/38717/1/Taxonomy_of_SQL_Injection_ML_Trends_amp_Open_Challenges.pdf
http://umpir.ump.edu.my/id/eprint/38717/2/Taxonomy%20of%20SQL%20Injection.pdf
http://umpir.ump.edu.my/id/eprint/38717/
https://doi.org/10.1109/ICSECS58457.2023.10256276
_version_ 1822923731861766144
score 13.23243

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