Abstract
The traditional malicious bot traffic detection technology is usually based on rule matching or statistical analysis, which is not flexible enough and has low detection accuracy. This article systematically analyzes the formation and characteristics of malicious bot traffic. And the WEB log traffic information is extracted, analyzed and selected as feature, finally we use support vector machine algorithm to train the malicious bot traffic detection model and the detection accuracy appears to be quite high. This is a good reference for applying machine learning to the field of cyber security.
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Acknowledgement
This research is supported by National Natural Science Foundation of China (No. 61772162), National Key R&D Program of China (No. 2018YFB0804102), Zhejiang Key R&D Program of China (No. 2018C01088).
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Wu, M., Wu, Z., Lv, H., Wang, J. (2019). A Method of Malicious Bot Traffic Detection. In: Vaidya, J., Zhang, X., Li, J. (eds) Cyberspace Safety and Security. CSS 2019. Lecture Notes in Computer Science(), vol 11983. Springer, Cham. https://doi.org/10.1007/978-3-030-37352-8_6
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DOI: https://doi.org/10.1007/978-3-030-37352-8_6
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