Determining Web Application Vulnerabilities Using Machine Learning Methods-Reference-Cited by-同舟云学术

Determining Web Application Vulnerabilities Using Machine Learning Methods

Published:2023-08-14 Issue: Volume: Page:
ISSN:
Container-title:2023 19th International Asian School-Seminar on Optimization Problems of Complex Systems (OPCS)
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Author:

Zhumabekova Aidana¹^ORCID,Matson Eric T²^ORCID,Karyukin Vladislav¹^ORCID,Zhumabekova Kuanysh³,Zhuandykov Berik⁴,Ussatova Olga⁵^ORCID,Telbayeva Tansholpan⁴

Affiliation:

1. Information Systems Al-Farabi Kazakh National University,Almaty,Kazakhstan

2. Purdue University,Department of Computer and Information Technology,West Lafayette,USA

3. Almaty Academy of the Ministry of Internal Affairs named M. Esbulatov,Almaty,Kazakhstan

4. G. Daukeev Almaty University of Energy and Communications,Almaty,Kazakhstan

5. Institute of Information and Computational Technologies, G.Daukeev Almaty University of Energy and Communications,Almaty,Kazakhstan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10275322/10275323/10275756.pdf?arnumber=10275756

Reference17 articles.

1. Comparative Study of Machine Learning Algorithms for Prediction of SQL Injections

2. Multi-Phase Algorithmic Framework to Prevent SQL Injection Attacks using Improved Machine learning and Deep learning to Enhance Database security in Real-time

3. SQL injection attack detection in network flow data

4. Comparative Analysis of SQL Injection Detection Approaches Using Machine Learning Methods;yudova;International Journal of Open Information Technologies T 11,2023

5. Detection of SQL Injection Attack Using Machine Learning Techniques: A Systematic Literature Review

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