Research Challenges and Performance of Clustering Techniques to Analyze NSL-KDD Dataset

Due to different malicious activities over Internet, there are major challenges to the research community as well as to the corporations. Many data mining techniques have been adopted for this purpose i.e. classification, clustering, association rule mining, regression, visualization etc. For this purpose clustering provides a better representation of network traffic in order to identify the type of data flowing through network. Clustering algorithms have been used most widely as an unsupervised classifier to organize and categorize data. In this paper, the authors have analyzed four different clustering algorithms using NSL-KDD dataset.

Provided by: International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) Topic: Data Management Date Added: Dec 2014 Format: PDF

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