Abstract
Recently, Internet has become an indispensable part of people’s daily lives, and a large number of service hosts provide services to users on the Internet. As a result, the security of these hosts that provide services on the public network is greatly threatened. If the attack suffered during the operation of the server host is not serious, it will affect the daily life of the user. However, once the server is severely attacked, the server will completely lose its ability to provide services. Therefore, network security has always been a hot issue of the Internet. The rise of machine learning and deep learning technology has given us a new solution. This technology not only has great advantages in dealing with large data sets, but also hopes to learn independently to deal with unknown attacks. Our paper will introduce some research for researchers’ reference in this area.
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Gao, MH., Meng, K. (2022). A Survey of Anomaly Traffic Detection Based on Machine Learning. In: Pan, JS., Balas, V.E., Chen, CM. (eds) Advances in Intelligent Data Analysis and Applications. Smart Innovation, Systems and Technologies, vol 253. Springer, Singapore. https://doi.org/10.1007/978-981-16-5036-9_20
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DOI: https://doi.org/10.1007/978-981-16-5036-9_20
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