The Research of Network Anomaly Detection Technology Based on Data Mining Article Swipe

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Chunhong Wu , Wenzhong Xia , Fengyun Liu ·

YOU? · · 2015 · Open Access · · DOI: https://doi.org/10.2991/icecee-15.2015.319

With the rapid development of computer network, various problems also arise, especially the network security problem.How to quickly and efficiently find a variety of network intrusion behavior, to ensure the safety of the system and network resource is very important.Intrusion detection is a proactive safety protection technology, to take the initiative to monitor and track the invasion, to protect the computer system, network system, and the safety of the information infrastructure has very important practical significance.In this paper, in light of the characteristics of the network environment, this paper proposes a new network anomaly detection based on data mining technology, the method of clustering analysis in data mining to extension, raise the efficiency of intrusion detection system, guaranteeing the security of the network.

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Condensed Matter Physics

Physics

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Anomaly detection Anomaly (physics) Computer science Data mining Data science Condensed matter physics Physics

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Type: article
Language: en
Landing Page: https://doi.org/10.2991/icecee-15.2015.319
PDF: https://download.atlantis-press.com/article/24804.pdf
OA Status: hybrid
References: 2
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OpenAlex ID: https://openalex.org/W1755510288

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DOI: https://doi.org/10.2991/icecee-15.2015.319

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Title: The Research of Network Anomaly Detection Technology Based on Data Mining

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Type: article

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Language: en

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Publication year: 2015

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Publication date: 2015-01-01

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Authors: Chunhong Wu, Wenzhong Xia, Fengyun Liu

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Landing page: https://doi.org/10.2991/icecee-15.2015.319

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PDF URL: https://download.atlantis-press.com/article/24804.pdf

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OA status: hybrid

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OA URL: https://download.atlantis-press.com/article/24804.pdf

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Concepts: Anomaly detection, Anomaly (physics), Computer science, Data mining, Data science, Condensed matter physics, Physics

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Cited by: 0

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References (count): 2

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Related works (count): 10

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