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- W3095405524 abstract "In today's contemporary era detection of network attacks has become the need of the hour due to increasing network traffic over the network. Data mining technique plays a vital role in searching network attacks and anomalies. These techniques help in selecting and refining useful and relevant information from large data sets. Data mining technique helps in classify relevant data for Intrusion Detection System. Intrusion Detection system generates alarms for the network traffic about the foreign invasions in the system. In the following paper we have used data mining classification techniques for intrusion detection in order to build a safe network. Random tree, Naive Bayes, J48 and Random forest machine learning classifier are used for classification. Comparison based on parameters like data accuracy, finding useful patterns, extracts useful information between the techniques." @default.
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- W3095405524 date "2020-09-25" @default.
- W3095405524 modified "2023-09-24" @default.
- W3095405524 title "Data mining Classification Techniques for Intrusion Detection System" @default.
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- W3095405524 doi "https://doi.org/10.1109/cicn49253.2020.9242642" @default.
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