A novel intrusion detection method based on clonal selection clustering algorithm

2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

Volumn , Issue , 2005, Pages 3905-3910

  Xian, Ji Qing ^a   Lang, Feng Hua ^a   Tang, Xian Lun ^b  

^a CHONGQING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^b CHONGQING UNIVERSITY   (China)

Author keywords

Anomaly detection; Artificial immune; Clonal selection algorithm; Fuzzy clustering; Fuzzy k means algorithm; Genetic algorithm

Indexed keywords

COMPUTATIONAL COMPLEXITY; EVOLUTIONARY ALGORITHMS; GENETIC ALGORITHMS; OPTIMIZATION; STOCHASTIC CONTROL SYSTEMS;

ANOMALY DETECTION; ARTIFICIAL IMMUNE; CLONAL SELECTION ALGORITHM; FUZZY CLUSTERING; FUZZY K-MEANS ALGORITHM;

FUZZY CONTROL;

EID: 28444479146     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. Caberera, J., Ravichandran, B., and Mehra, R.K., "Statistical modeling for network intrusion detection", Proceeding of Modeling, Analysis and Simulation of Computer and Telecommunication System, San Francisco, pp. 466-473, Sept. 2000.
2. Krugeel, C., Mutz, D., Robertson, W., and Valeur, F., "Bayesian Event classification for intrusion detection", Proceeding of Computer Security Applications Conference, Las Vegas, pp. 14-23, Dec. 2003.
3. White G B, Fisch E A, and Pooch U W, "Cooperating security managers: a peer based intrusion detection system", IEEE Network, Vol 10, No. 1, pp. 20-23, 1996.
4. Sung-Baecho, "Incorporating soft computing techniques into a probabilistic intrusion detection system", IEEE transactions on System, Man and Cybernetics(Part C), Vol 32, No. 2, pp. 154-160, 2004.
5. Hochberg J, Jackson K, and Staltings C, "NADIR: an automated system for detecting network intrusion and misuse", Computer and Security, Vol 12, No. 3, pp. 235-248, 2003.
6. Dasgupta, D., and Gonzalez, F., "An immunity-based technique to characterize intrusions in computer networks", IEEE transactions on Evolutionary Computation, Vol 6, No. 3, pp. 281-291, Jun. 2002.
7. Qiao, Y, X.W., and Bin, Y., Ge, S., "Anomaly intrusion detection method based on HMM", Electronics Letters, Vol 38, No. 13, pp. 663-664, Jun. 2002,.
8. He, D., and Leung, H., "CFAR intrusion detection method based on support vector machine prediction", Proceeding of CIMSA2004, Boston, pp. 10-15, Jul. 2004.
9. Jeme N.K., "Towards a Network Theory of the Immune System", Ann. Immunol, pp:373-389, 1974.
10. Castro L N, and Von Zuben F J, "Learning and optimization using the clone selection principle", IEEE Transaction On Evolutionary Computation, Vol 6, No. 3, pp. 239-251, 2002.
11. Li Jie, Gao Xinbo, and Jiao Licheng, "A novel clustering method with network structure based on clonal algorithm", Canada, Proceeding of ICASSP2004, Canada, pp. 793-796, May 2004.
12. Portnoy L, Eskin E, and Stolfo J, "Intrusion detection with unlabeled data using clustering", Proceedings of ACM CSS Workshop on Data Mining Applied to Security, Philadelphia, 2001.
13. KDD CUP99 data set, http://kdd.ics.uci.edu/databases/kddcup99/kddcup99. html, 1999.