Performance Study on Malicious Program Prediction Using Classification Techniques
|K. Thyagarajan1 , N. Vaishnavi2|
1 Dept of Computer Science, AVC College, Mayiladuthurai, India.
2 Dept of Computer Science, AVC College, Mayiladuthurai, India.
Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-5 , Page no. 59-64, May-2018
Online published on May 31, 2018
Copyright © K. Thyagarajan, N. Vaishnavi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: K. Thyagarajan, N. Vaishnavi, “Performance Study on Malicious Program Prediction Using Classification Techniques”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.59-64, 2018.
MLA Style Citation: K. Thyagarajan, N. Vaishnavi "Performance Study on Malicious Program Prediction Using Classification Techniques." International Journal of Computer Sciences and Engineering 6.5 (2018): 59-64.
APA Style Citation: K. Thyagarajan, N. Vaishnavi, (2018). Performance Study on Malicious Program Prediction Using Classification Techniques. International Journal of Computer Sciences and Engineering, 6(5), 59-64.
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|Data mining is that the method of move queries and extracting patterns, typically antecedently unknown from giant quantities of data using pattern matching several applications in security as well as for national security likewise as for cyber security. Research focus on Detecting Malicious Packet uses weka. Once network routers are a unit subverted to act during a malicious fashion. To observe the existence of compromised routers during a network, then take away them from the routing fabric. Our approach is to separate the matter into three sub-problems: 1) crucial the traffic data to record upon that to base the detection, 2) synchronizing routers to gather traffic data and distributing this data among them thus detection will occur, and 3) taking countermeasures once detection happens. Experimental results show that ready to observe and isolate a spread of malicious router actions with acceptable overhead and quality. Our work has ready to tolerate attacks on key network infrastructure elements.|
|Key-Words / Index Term :|
|Data mining, Malicious program, JRip, PART, OneR, Malicious classifier, classification, WEKA tool|
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