SQL Injection Attack Detection Using Machine Learning Techniques
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-5015-7_13
Reference14 articles.
1. Yadav D, Gupta D, Singh D, Kumar D, Sharma U (2018) Vulnerabilities and security of web applications. In: 2018 4th international conference on computing communication and automation (ICCCA), 14 Dec 2018. IEEE, pp 1–5
2. Shahid J, Hameed MK, Javed IT, Qureshi KN, Ali M, Crespi N (2022) A comparative study of web application security parameters: current trends and future directions. Appl Sci 12(8):4077
3. Chen D, Yan Q, Wu C, Zhao J (2021) SQL injection attack detection and prevention techniques using deep learning. J Phys Conf Ser 1757(1):012055
4. Gandhi N, Patel J, Sisodiya R, Doshi N, Mishra S (2021) A CNN-BiLSTM based approach for detection of SQL injection attacks. In: 2021 international conference on computational intelligence and knowledge economy (ICCIKE), 17 Mar 2021. IEEE, pp 378–383
5. Li Q, Li W, Wang J, Cheng M (2019) A SQL injection detection method based on adaptive deep forest. IEEE Access 1(7):145385–14594
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