An unsupervised anomaly intrusion detection algorithm based on swarm intelligence

2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

Volumn , Issue , 2005, Pages 3965-3969

  Feng, Yong ^a   Wu, Zhong Fu ^a   Wu, Kai Gui ^a   Xiong, Zhong Yang ^a   Zhou, Ying ^a  

^a CHONGQING UNIVERSITY   (China)

Author keywords

Anomaly intrusion detection; Clustering; Swarm Intelligence

Indexed keywords

COMPUTER SIMULATION; DATA REDUCTION; MATHEMATICAL MODELS; PROBLEM SOLVING; SECURITY OF DATA; TREES (MATHEMATICS);

ANOMALY INTRUSION DETECTION; CLUSTERING; SWARM INTELLIGENCE;

ALGORITHMS;

EID: 28444457043     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (17)

1. S. Forrest, A. Perelson, L. Allen, and R. Cherukury, "Self-nonself discrimination in a computer", In Proceeding of the IEEE Symp. on research in security and privacy, 1994.
2. S. Singh, "Anomaly detection using negative selection based on the rcontiguous matching rule", In 1st International Conference on Artificial Immune Systems (ICARIS), pp. 99-106, 2002.
3. T. Lane, and C. E. Brodley, "An application of machine learning to anomaly detection", In Proc. 20th NIST-NCSC National Information Systems Security Conference, 1997.
4. T. Lane, and C. E. Brodley, "Sequence matching and learning in anomaly detection for computer security", In AI Approaches to Fraud Detection and Risk Management, pp. 43-49, 1997.
5. M. Mahoney, and P. Chan, "Learning nonstationary models of normal network traffic for detecting novel attacks", In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 23-26, 2002.
6. W. Fan, W. Lee, M. Miller, S. Stolfo, and P. Chan, "Using artificial anomalies to detect unknown and known network intrusions", In Proceedings of the first IEEE International conference on Data Mining, 2001.
7. F. Gonzalez, and D. Dasgupta, "Neuro-immune and self-organizing map approaches to anomaly detection: A comparison", In First International Conference on Artificial Immune Systems, September, 2002.
8. Portnoy L, Eskin E, and Stolfo S J, "Intrusion detection with unlabeled data using clustering", In Proceeding of ACM CSS Workshop on Data Mining Applied to Security (DMSA2001), Philadelphia, 2001.
9. Bonabeau E, Dorigo M, and Theraulaz G, Swarm Intelligence: From Natural to Artificial Systems, Oxford University Press, New York, 1999.
10. Gianni Di Caro, and Marco Dorigo, "AntNet: Distributed Stigmergetic Control for Communications Networks", Journal of Artificial Intelligence Research, pp. 317-355, 1998.
11. M. Dorigo, E. Bonabeau, G. Theralulaz, "Ant Algorithms and stigmergy", Future Generation Computer Systems, pp. 851-871, 2000.
12. Deneuhourg J L, Goss S, and Franks N, "The Dynamics of Collective Sorting: Robot-Like Ant and Ant-Like Robot", In Proceedings First Conference on Simulation of Adaptive Behavior: From Animals to Animats, Cambridge, pp. 356-365, 1991.
13. E.Lumer, and B.Faieta, "Diversity and adaptation in populations of clustering ants", Proceedings of the Third International Conference on Simulation of Adaptive Behavior: From Animals to Animats, Cambridge, pp. 499-508, 1994.
14. B. Wu, and Z. Shi, "A Clustering Algorithm Based on Swarm Intelligence", IEEE International Conferences on Info-tech & Info-net Proceeding, Beijing, pp.58-66, 2001.
15. R. Duda, and P. Hart, Pattern Classification and Scene Analysis. John Wiley & Sons Press, New York, 1973.
16. KDD99, "KDD99 cup dataset", http://kdd.ics.uci.edu/databases/ kddcup99, 1999.
17. E. Eskin, A. Arnold, and M. Prerau, "A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data", Published in Data Mining for Security Applications, Kluwer, 2002.