A deep learner model for multi-language webshell detection-Reference-Cited by-同舟云学术

A deep learner model for multi-language webshell detection

Published:2022-10-18 Issue:1 Volume:22 Page:47-61
ISSN:1615-5262
Container-title:International Journal of Information Security
language:en
Short-container-title:Int. J. Inf. Secur.

Author:

Hannousse Abdelhakim^ORCID,Nait-Hamoud Mohamed Cherif,Yahiouche Salima

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality,Information Systems,Software

Link

https://link.springer.com/content/pdf/10.1007/s10207-022-00615-5.pdf

Reference34 articles.

1. Ahsan, M.M., Mahmud, M.A.P., Saha, P.K., Gupta, K.D., Siddique, Z.: Effect of data scaling methods on machine learning algorithms and model performance. Technologies (2021). https://doi.org/10.3390/technologies9030052

2. Allamanis, M.: The adverse effects of code duplication in machine learning models of code. In: Proceedings of the 2019 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software. 143–153. Onward! 2019, ACM, New York, NY, USA (2019). https://doi.org/10.1145/3359591.3359735

3. Avast: Avast software: Free antivirus is your first step to online freedom. [online], available: (1995). https://www.avast.com/

4. Bengfort, B., Bilbro, R., Ojeda, T.: Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning, 1st edn. O’Reilly Media Inc. (2018)

5. Cui, H., Huang, D., Fang, Y., Liu, L., Huang, C.: Webshell detection based on random forest–gradient boosting decision tree algorithm. In: 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC). pp. 153–160. IEEE CS (2018). https://doi.org/10.1109/DSC.2018.00030

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