Matches in SemOpenAlex for { <https://semopenalex.org/work/W3213692590> ?p ?o ?g. }
- W3213692590 endingPage "152396" @default.
- W3213692590 startingPage "152379" @default.
- W3213692590 abstract "Anomalies could be the threats to the network that has ever/never happened. To detect and protect networks against malicious access is always challenging even though it has been studied for a long time. Due to the evolution of network in both new technologies and fast growth of connected devices, network attacks are getting versatile as well. Comparing to the traditional detection approaches, machine learning is a novel and flexible method to detect intrusions in the network, it is applicable to any network structure. In this paper, we introduce the challenges of anomaly detection in the traditional network, as well as the next generation network, and review the implementation of machine learning in anomaly detection under different network contexts. The procedure of each machine learning type is explained, as well as the methodology and advantages presented. The comparison of using different machine learning models is also summarised." @default.
- W3213692590 created "2021-11-22" @default.
- W3213692590 creator A5039353678 @default.
- W3213692590 creator A5053577808 @default.
- W3213692590 creator A5078824132 @default.
- W3213692590 creator A5083386976 @default.
- W3213692590 creator A5084794908 @default.
- W3213692590 creator A5085279545 @default.
- W3213692590 date "2021-01-01" @default.
- W3213692590 modified "2023-10-14" @default.
- W3213692590 title "Machine Learning in Network Anomaly Detection: A Survey" @default.
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