PERCEIVING INTRUSION USING DATA MINING TECHNIQUES
Sri Vasavi College, Erode Self-Finance Wing 3rd February 2017 National Conference on Computer and Communication NCCC’17
In the soviet most of the activities are done through Internet. The increased usage of internet has leads to the unauthorized access of the information. There are several types of attacks present in the current world. Now a days Intrusion detection is the most common challenge of the information security. Regarding perceiving intrusion so many techniques are present but data mining is the tremendous approach for detecting intrusion. In this paper converse the numerous data mining approaches for perceiving intrusion on the network based on accuracy, detection rate and alarm.
1. Rowayda A. Sadek, M. Sami Soliman and Hagar S. Elsayed“Effective Anomaly Intrusion Detection System based on NeuralNetwork with Indicator Variable and Rough set Reduction” IJCIinternational Journal of Computer Science Issue, Vol,10, Issue 6,No 2, 2013 2. Ahmed A. Elngar, Dowlat A. El A. Mohamed and Fayed F. M.Ghaleb “A Real-Time Anomaly Network Intrusion DetectionSystem with High Accuracy” 2013 Inf. Sci. Lett. 2, No. 2, 49-56(2013) 3.HeshamAltwaijry ,SaeedAlgarny “Bayesian based intrusiondetection system” 2012 Journal of King Saud University 2012 4.Renuka Devi Thanasekarn “A Robust and Efficient Real TimeNetwork Intrusion Detection System Using Artificial NeuralNetwork In Data Mining” 2011 International Journal of InformationTechnology Convergence and Services(IJITCS) Vol. 1, No. 4, 2011 5. Naveen N C, Dr. R Srinivasan , Dr. S Natarajan “A UnifiedApproach for Real Time Intrusion Detection Using Intelligent DataMining Techniques” 2011, IJCA Special Issue 2011 6. Tao Peng, WanliZuo “Data Mining for Network IntrusionDetection System in Real Time” IJCSNS International Journal ofComputer Science and Network Security, VOL.6 No.2B, February2006 7.https://www.reference.com/technology/internet-communication-a0b802f85dc624db 8. http://www.kdnuggets.com/2015/05/top-10-data-mining-algorithms-explained.html
Data mining, intrusion detection, classification, clustering