Anomaly detection based intrusion detection

Proceedings - Third International Conference onInformation Technology: New Generations, ITNG 2006

Volumn 2006, Issue , 2006, Pages 420-425

  Novikov, Dima ^a   Yampolskiy, Roman V ^b   Reznik, Leon ^a  

^a Rochester Institute of Technology   (United States)

^b the State University of New York   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANOMALY DETECTION; INTRUSION DETECTION; RESEARCHERS;

COMPUTER CRIME; COMPUTER SIMULATION; INFORMATION TECHNOLOGY; NEURAL NETWORKS; PROBLEM SOLVING; RESEARCH AND DEVELOPMENT MANAGEMENT;

SECURITY OF DATA;

EID: 33750804406     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ITNG.2006.33     Document Type: Conference Paper

References (9)

1. DARPA, Intrusion Detection Evaluation. MIT Lincoln Laboratory, 1998 (http://www.ll.mit.edu/ist/ideval).
2. Hettich, S. and S.D. Bay, The UCIKDD Archive. University of California, Department of Information and Computer Science, 1999.
3. KDD, http://wwwcse.ucsd.edu/users/elkan/clresults.html. KDD Cups 99 - Intrusion Detection Contest, 1999.
4. Lee, W., S. Stolfo, and K. Mok, Mining in a Data-Flow Environment: Eperience in Network Intrusion Detection. In Proceedings of the 5th ACM SIGKDD, 1999.
5. Lee, W., S.J. Stolfo, and K.W. Mok, A Data Mining Framework for Building Intrusion Detection Models. IEEE Symposium on Security and Privacy, 1999.
6. Mukkamala, S., G. Janoski, and A. Sung, Intrusion Detection Using Neural Networks and Support Vector Machine. IEEE, 2002.
7. Planquart, J., Application of Neural Networks to Intrusion Detection. SANS Institute, 2001.
8. Rhodes, B., J. Mahaffey, and J. Cannady, Multiple Self-Organizing Maps for Intrusion Detection. GIT Information Technology and Telecommunications Laboratorys, 1999.
9. Sabhnani, M. and G. Serpen, Application of Machine Learning Algorithms to KDD Intrusion Detection Dataset within Misuse Detection Context. EECS, University of Toledo, 2003.