Abstract
Content Delivery Network (CDN) is an emerging network acceleration technology and an important infrastructure on the Internet. However, there are currently a large number of domestic domain names that use CDN services in confusion, setting up numerous obstacles to the management of domestic basic resources, which in turn leads to potential security risks for the network security of the entire country. Currently, CDN domain names are detected mainly by using the character features of CDN domain names, HTTP keywords, and DNS records, and the recognition range is very limited. In response to this problem, this article introduces the basic principles and workflow of CDN in detail, analyzes the characteristics and related attributes of CDN domain names, and uses random forest classification algorithms to establish a CDN service detection model based on machine learning., It mainly detects CDN domain names and CDN acceleration nodes, and verifies the accuracy of the proposed detection method through experimental analysis, and explains the necessity of CDN service detection.
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Wang, Y., Wang, H. (2023). CDN Service Detection Method Based on Machine Learning. In: Tang, L.C., Wang, H. (eds) Big Data Management and Analysis for Cyber Physical Systems. BDET 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 150. Springer, Cham. https://doi.org/10.1007/978-3-031-17548-0_15
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DOI: https://doi.org/10.1007/978-3-031-17548-0_15
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