Paper The following article is Open access

SQL Injection Attack Detection and Prevention Techniques Using Deep Learning

, , and

Published under licence by IOP Publishing Ltd
, , Citation Ding Chen et al 2021 J. Phys.: Conf. Ser. 1757 012055 DOI 10.1088/1742-6596/1757/1/012055

1742-6596/1757/1/012055

Abstract

Web application brings us convenience but also has some potential security problems. SQL injection attacks topped the list of Top 10 Network Security Problems released by OWASP, and the detection technology of SQL injection attacks has been one of the hotspots of network security research. In this paper, we propose a SQL injection detection method that does not rely on background rule base by using a natural language processing model and deep learning framework on the basis of comprehensive domestic and international research. The method can improve the accuracy and reduce the false alarm rate while allowing the machine to automatically learn the language model features of SQL injection attacks, greatly reducing human intervention and providing some defense against 0day attacks that never occur.

Export citation and abstract BibTeX RIS

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

Please wait… references are loading.
10.1088/1742-6596/1757/1/012055