Detecting SQL Injection On Web Application Using Deep Learning Techniques: A Systematic Literature Review

被引:3
作者
Muslihi, Muhammad Takdir [1 ]
Alghazzawi, Daniyal [1 ]
机构
[1] King Abdulaziz Univ, Fac Comp & Informat Technol, Dept Informat Syst, Jeddah 21589, Saudi Arabia
来源
2020 THIRD INTERNATIONAL CONFERENCE ON VOCATIONAL EDUCATION AND ELECTRICAL ENGINEERING (ICVEE): STRENGTHENING THE FRAMEWORK OF SOCIETY 5.0 THROUGH INNOVATIONS IN EDUCATION, ELECTRICAL, ENGINEERING AND INFORMATICS ENGINEERING | 2020年
关键词
SQL Injection; Web Application; Deep Learning;
D O I
10.1109/icvee50212.2020.9243198
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Based on OWASP, code injection is one of the top lists of security risks. Structured Query Language (SQL) Injection is one of these types of attacks. SQL injection attack is an attack by spoofing the server to execute malicious code. The main object of this paper is to identify relevant works about deep learning methods to detect SQL-Injection on web applications. To achieve that, we conduct a survey review of the literature. In this study, we provide a review of 14 studies using deep learning algorithms to detect SQL Injection on web applications and it provides a comparison between them. Deep learning has great potential in threat intelligence detection.
引用
收藏
页数:6
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