Security in Data Mining-A Comprehensive Survey


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Niranjan, A. and Nitish, A. and Deepa Shenoy, P. and Venugopal, K.R. (2016) Security in Data Mining-A Comprehensive Survey. Global Journal of Computer Science and Technology, 16 (5). ISSN 0975-4172


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Data mining techniques, while allowing the individuals to extract hidden knowledge on one hand, introduce a number of privacy threats on the other hand. In this paper, we study some of these issues along with a detailed discussion on the applications of various data mining techniques for providing security. An efficient classification technique when used properly, would allow an user to differentiate between a phishing website and a normal website, to classify the users as normal users and criminals based on their activities on Social networks (Crime Profiling) and to prevent users from executing malicious codes by labelling them as malicious. The most important applications of Data mining is the detection of intrusions, where different Data mining techniques can be applied to effectively detect an intrusion and report in real time so that necessary actions are taken to thwart the attempts of the intruder.

Item Type: Article
Uncontrolled Keywords: anamoly detection; classification; intrusion detection system; outlier detection; privacy preserving data minig
Subjects: Faculty of Engineering > Computer Science & Information Science Engineering
Divisions: University Visvesvarayya College of Engineering > Department of Computer Science and Information Science Engineering
Depositing User: Ms Laxmi Kamble
Date Deposited: 15 Sep 2021 10:06
Last Modified: 15 Sep 2021 10:06

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