A Survey of Clustering and Classification on Security in Data Mining

Data mining is the process that extracts classifies andanalyzes valid and useful information from large volumes of dataprovided by multiple sources. The data mining has been widelyapplied into various areas, one of which is to investigate potentialsecurity threats. In the literature, various data mining techniquessuch as classification and clustering have been proposed to detectintrusions, DoS attacks, and malware. This paper surveysdifferent data mining techniques applied to detect securitythreats and analyzes their advantages and disadvantages.Through comparison, we discuss open research issues aboutsecurity-related data mining and propose future research focus.