Discriminating and visualizing anomalies using negative selection and self-organizing maps

GECCO 2005 - Genetic and Evolutionary Computation Conference

Volumn , Issue , 2005, Pages 297-304

  González, Fabio A ^a   Rojas, Diego Alexander ^a   Galeano, Juan Carlos ^a   Veloza Suan, Angélica ^a  

^a UNIVERSIDAD NACIONAL DE COLOMBIA   (Colombia)

Author keywords

Anomaly detection; Anomaly visualization; Artificial immune systems; Negative selection; Self organizing maps

Indexed keywords

SELF ORGANIZING MAPS; TOPOLOGY;

ANOMALY DETECTION; ANOMALY VISUALIZATION; ARTIFICIAL IMMUNE SYSTEMS; NEGATIVE SELECTION;

IMMUNOLOGY;

EID: 32444446071     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1068009.1068058     Document Type: Conference Paper

References (27)

1. U. Aickelin, P. Bentley, S. Cayzer, J. Kim, and J. McLeod.Danger theory: The link between AIS and IDS?In J. Timmis, P. Bentley, and E. Hart, editors, Proceedings of the end International Conference on Artificial Immune Systems, volume 2787 of Lecture Notes in Computer Science, pages 147-155. Springer-Verlag, September 2003.
2. S. Axelsson.Visualising intrusions: Watching the Webserver,.In proceedings of the 19th IFIP International Information Security Conference. (SEC2004), Tolouse, France, Aug 2004.
3. C. A. Coello Coello and N. Cruz Cortés.A parallel implementation of the artificial immune system to handle constraints in genetic algorithms: preliminary results.In D. B. Fogel, M. A. El-Sharkawi, X. Yao, G. Greenwood, H. Iba, P. Marrow, and M. Shackleton, editors, Proceedings of the 2002 Congress on Evolutionary Computation CEC2002, pages 819-824, USA, 2002.
4. D. Dasgupta.Artificial immune systems and their applications.Bpringer-Verlag, New York, 1999.
5. D. Dasgupta.Immunity-based intrusion detection system: a general framework.In Proceedings of the Send national information systems security conference (NISSC), pages 147-160, Oct. 1999.
6. D. Dasgupta and S. Forrest.Tool breakage detection in milling operations using a negative-selection algorithm.Technical Report CS95-5, Department of Computer Science, University of New Mexico, 1995.
7. D. Dasgupta and S. Forrest.Novelty detection in time series data using ideas from immunology.In J. F. C. Harris, editor, Proceedings of the 5th International Conference on Intelligent Systems, pages 82-87, Gary, NC, June 1996. ISCA.
8. D. Dasgupta and S. Forrest.An anomaly detection algorithm inspired by the immune system.In D. Dasgupta, editor, Artificial immune systems and their applications, pages 262-277. Springer-Verlag, New York, 1999.
9. L. N. de Castro and J. Timmis.Artificial Immune Systems: A New Computational Approach.Springer-Verlag, London, UK, 2002.
10. P. D'haeseleer, S. Forrest, and P. Helman.An immunological approach to change detection: algorithms, analysis and implications.In J. McHugh and G. Dinolt, editors, Proceedings of the 1996 IEEE Symposium on Computer Security and Privacy pages 110-119, USA, 1996. IEEE Press.
11. R. F. Erbacher.Glyph-based generic network visualization.In Proceedings of the SPIE '2002 Conference on Visualization and Data Analysis, pages 228-237, San Jose, CA, January 2002.
12. S. Forrest, A. Perelson, L. Allen, and R. Cherukuri.Self-nonself discrimination in a computer.In Proceedings IEEE Symposium on Research in Security and Privacy, pages 202-212, Los Alamitos, CA, 1994. IEEE Computer Society Press.
13. L. Girardin and D. Brodbeck.A visual approach for monitoring logs.Proceedings of the Twelth Systems Administration Conference (LISA XII) (USENIX Association: Berkeley, CA), page 299, 1998.
14. F. González and D. Dasgupta.Anomaly detection using real-valued negative selection. Genetic Programming and Evolvable Machines, 2003.to be published.
15. F. González, D. Dasgupta, and R. Kozma.Combining negative selection and classification techniques for anomaly detection.In D. B. Fogel, M. A. El-Sharkawi, X. Yao, G. Greenwood, H. Iba, P. Marrow, and M. Shackleton, editors, Proceedings of the 2002 Congress on Evolutionary Computation CEC2002, pages 705-710, USA, May 2002. IEEE Press.
16. F. González, D. Dasgupta, and F. Niño.A randomized real-valued negative selection algorithm.In J. Timmis, P. Bentley, and E. Hart, editors, Proceedings of the 2nd International Conference on Artificial Immune Systems, volume 2787 of Lecture Notes in Computer Science, pages 261-272. Springer, September 2003.
17. P. Harmer, G. Williams, P.D.and Gnusch, and G. Lamont.An Artificial Immune System Architecture for Computer Security Applications.IEEE Transactions on Evolutionary Computation, 6(3):252-280, June 2002.
18. S. Haykin.Neural networks : a comprehensive foundation-Macmillan, New York, 1994.
19. S. Hofmeyr and S. Forrest.Architecture for an artificial immune ayatem.Evolutionary Computation, 8(4):443-473, 2000.
20. N. K. Jerne.Towards a network theory of the immune system.Ann Immunol. (Inst. Pasteur), 125C:373-389, 1974.
21. J. O. Kephart.A biologically inspired immune system for computers.In R. A. Brooks and P. Maes, editors, Proceedings of the 4th International Workshop on the Synthesis and Simulation of Living Systems Artificial LifeIV, pages 130-139, Cambridge, MA, USA, July 1994. MIT Press.
22. T. Kohonen.Self-Organizing Maps, volume 30 of Springer Series in Information Sciences.Springer, Berlin, Heidelberg, 1995. (Second Extended Edition 1997).
23. I.-V. Onut, B. Zhu, and A. A. Ghorbani. A novel visualization technique for network anomaly detection.In Proceedings of the Second Annual Conference on Privacy, Security and Trust (PST'04), New Brunswick, Canada, oct 2004.
24. A. Secker, A. Freitas, and J. Timmis.A danger theory approach to web mining.In J. Timmis, P. Bentley, and E. Hart, editors, Proceedings of the end International Conference on Artificial Immune Systems, volume 2787 of Lecture Notes in Computer Science, pages 156-167. Springer-Verlag, September 2003.
25. S. T. Teoh, T. J. Jankun-Kelly, K.-L. Ma, and S. F. Wu.Visual data analysis for detecting flaws and intruders in computer network systems.IEEE Computer Graphics and Applications, 24(5), Sep/Oct 2004.
26. A. Tyrrell.Computer know thy self! : a biological way to look at fault tolerance.In Proceedings of the end Euromicro/Ieee workshop on Dependable Computing Systems, pages 129-135, Milan, 1999.
27. P. D. Williams, K. P. Anchor, J. L. Bebo, G. H. Gunsch, and G. D. Lamont.CDIS: Towards a computer immune system for detecting network intrusions. Lecture Notes in Computer Science, 2212:117-133, 2001.