SIDNet: A SQL Injection Detection Network for Enhancing Cybersecurity
- Title
- SIDNet: A SQL Injection Detection Network for Enhancing Cybersecurity
- Creator
- Muduli D.; Shookdeb S.; Zamani A.T.; Saxena S.; Kanade A.S.; Parveen N.; Shameem M.
- Description
- SQL (Structured Query Language) injection is one of the most prevalent and dangerous forms of cyber-attacks, posing significant threats to database management systems and the overall security of web applications. By exploiting vulnerabilities in web applications, attackers can execute malicious SQL statements, potentially compromising the integrity and confidentiality of critical data. To combat these threats, in this study, we introduce two novel CNN models, SIDNet-1 (SQL Injection-attack Detection Network-1) and SIDNet-2 (SQL Injection-attack Detection Network-2), specifically designed for the classification of SQL injection attacks to bolster web application security. Our comprehensive evaluation includes a comparison of the performance of these customized CNN models against traditional machine learning approaches, highlighting improvements in classification accuracy and reductions in false alarm rates. The proposed models have been experimented with two publicly available dataset SQLI (SQL-Injection) and SQLV2 (SQL-Injection version2). Specifically, SIDNet-1 achieves an impressive accuracy of 98.02% on the SQLI dataset, while SIDNet-2 closely follows with 97.54%. Furthermore, on the SQLIV2 dataset, SIDNet-1 attains 97.77%, and SIDNet-2 achieves 97.83% accuracy respectively. 2013 IEEE.
- Source
- IEEE Access, Vol-12, pp. 176511-176526.
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- CNN; cyber security; SIDNet; SQLI
- Coverage
- Muduli D., C. V. Raman Global University, Department of Computer Science and Engineering, Odisha, Bhubaneswar, 752054, India; Shookdeb S., C. V. Raman Global University, Department of Computer Science and Engineering, Odisha, Bhubaneswar, 752054, India; Zamani A.T., Northern Border University, Department of Computer Science, Arar, 91431, Saudi Arabia; Saxena S., CHRIST University, Department of Computer Science, Bengaluru, India; Kanade A.S., Dr. Vishwanath Karad-MIT-World Peace University, Department of Computer Science and Applications, Pune, 411038, India; Parveen N., Koneru Lakshmaiah Education Foundation Deemed to Be University, Department of Computer Science and Engineering, Andhra Pradesh, Guntur, 522302, India; Shameem M., King Fahd University of Petroleum and Minerals, Interdisciplinary Research Center for Intelligent and Secure Systems, Dhahran, 31261, Saudi Arabia
- Rights
- Restricted Access
- Relation
- ISSN: 21693536
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Muduli D.; Shookdeb S.; Zamani A.T.; Saxena S.; Kanade A.S.; Parveen N.; Shameem M., “SIDNet: A SQL Injection Detection Network for Enhancing Cybersecurity,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/12963.