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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 7    
Website: http://www.ijser.org
scirp IJSER >> Volume 2, Issue 7, July 2011 Edition
Survey On Data Mining Techniques In Intrusion Detection
Full Text(PDF, 3000)  PP.  
Amanpreet Chauhan, Gaurav Mishra, Gulshan Kumar
Network Intrusion, Decision Trees, Naïve Bayes, Fuzzy Logic, Support Vector Machines, Data Clustering, Data Mining.
Intrusion Detection (ID) is the main research area in field of network security. It involves the monitoring of the events occurring in a computer system and its network. Data mining is one of the technologies applied to ID to invent a new pattern from the massive network data as well as to reduce the strain of the manual compilations of the intrusion and normal behavior patterns. Keeping in mind, data mining techniques are practiced significantly intrusion detection and prevention. This article reviews the current state of art Data mining techniques with ID in brief and highlights its advantages and disadvantages.
[1] Alexander D. Korzyk. A Forecasting Model For Internet Security Attacks.

[2] Simon Hansman and Ray Hunt (2004). A Taxonomy of Network and Computer Attacks

[3] Mrityunjaya Panda and Manas Ranjan Patra. A Comparative Study of Data Mining Algorithms for Intrusion Detection.

[4] Eric Knight (2000). Computer Vulnerabilities

[5] Jose F. Nieves (2009). Data Clustering for Anomaly Detection in Network Intrusion Detection.

[6] Ian H. Witten and Eibe Frank. Data Mining : Practical Machine Learning Tools and Techniques.

[7] Chih-Fong Tsai, Yu-Feng Hsu, Chia-Ying Lin, Wei-Yang Lin (2009). Intrusion detection by Machine Learning : A Review

[8] Srinivas Mukkamala, Andrew H. Sung, Ajith Abraham (2004). Intrusion Detection Using an Ensemble of Intelligent Paradigms .

[9] V. Vapnik (1998). Statistical Learning Theory. New York: John Wiley

[10] H. Zimmerman (2001). Fuzzy Set Theory and Its Applications. Kluwer Academic Publishers.

[11] Ajith Abraham and Ravi Jain. Soft Computing Models for Network Intrusion Detection Systems.

[12] Mrutyunjaya Panda, Manas Ranjan Patra. A Comparative Study of Data Mining Algorithms for Intrusion Detection.

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