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Authors
Affiliations
1 Marathwada Mitra Mandal's College of Engineering Pune, IN
2 Marathwada Mitra Mandal's College of Engineering Pune (Savitribai Phule Pune University Maharashtra), IN
3 Shivaji University, IN
Source
Software Engineering, Vol 8, No 3 (2016), Pagination: 66-69
Abstract
Network is information system implemented with a collection of interconnected components. Network Security is nothing but any activities designed to protect your network. Intrusion poses a serious security risk in a network environment. Anomaly based intrusion detection in networks is the problem of finding exceptional patterns in network traffic that do not conform to the expected normal behavior. An intrusion attempt is an unauthorized attempt to access the information or render a system unreliable or unusable. Therefore, it represents one of the efficient Data Mining algorithm called K-Means clustering and Naive Bayes classification for Anomaly Based Network Intrusion detection. This technique performs better in terms of detection rate.
Keywords
Network Intrusion Detection, Data Mining, K-Means Clustering, Naive Bayes Classifier, Detection Rate.
