Artificial dendritic cells algorithm for online break-in fraud detection

Proceedings - International Conference on Developments in eSystems Engineering, DeSE 2009

Volumn , Issue , 2009, Pages 181-189

  Huang, R ^a   Tawfik, H ^a   Nagar, A K ^a  

^a LIVERPOOL HOPE UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIGEN RECEPTORS; ARTIFICIAL IMMUNE SYSTEM; COMPUTER SECURITY; DENDRITIC CELLS; DENTRITIC CELLS; FALSE ALARMS; FRAUD DETECTION; HIGH DETECTION RATE; HIGH DIMENSIONAL DATA; ONLINE VIDEO;

ANTIGENS; CLUSTERING ALGORITHMS; COMPUTER APPLICATIONS; DENDRIMERS; SENSITIVITY ANALYSIS;

CRIME;

EID: 77949574827     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/DeSE.2009.59     Document Type: Conference Paper

References (19)

1. Forrest, S, Perelson, A, Allen, L and Cherukuri, R (1994). "Self-Nonself Discrimination in a Computer". In Proc. of IEEE Symposium on Research in Security and Privacy. Oakland, USA, pp. 202-212.
2. Jerne, N. (1974) "Towards a network theory of the immune system," Annals of Immunology, vol. 125, pp. 373-389)
3. de Castro, L. N. and F. J. Von Zuben. (2000) "The clonal selection algorithm with engineering applications". In Proc. of GECCO" 00. Workshop on Artificial Immune Systems and Their Applications. Pages 36-37
4. P. Matzinger., (1994), Tolerance, danger and the extended family. Annual Reviews in Immunology, 12:991-1045.
5. P. Matzinger, (2002), "The Danger Model: A Renewed Sense of Self, Science, 296, pp. 301-305.
6. Greensmith, J., Aickelin, U. and Cayzer, S. (2005) Introducing Dendritic Cells as a Novel Immune-Inspired Algorithm for Intrusion Detection, In Proc. of ICARIS-05, Springer-Verlag, pp. 153-167.
7. U. Aickelin, P. Bentley, S. Cayzer, J. Kim, and J. (2003) McLeod. Danger theory: The link between AIS and IDS. In Proc. of the 2nd International Conference on Artificial Immune Systems (ICARIS), LNCS 2787, pp. 147-155. Springer-Verlag.
8. J. Greensmith, U. Aickelin, and J. Feyereisl. (2008) The DCA SOMe comparison: A comparative study between two biologically-inspired algorithms. Evolutionary Intelligence: Special Issue on Artificial Immune Systems, accepted for publication.
9. J. Greensmith, U. Aickelin, and G. Tedesco. (2008) Information fusion for anomaly detection with the DCA. Information Fusion, in print.
10. J. Greensmith, J. Twycross, and U. Aickelin. (2006) Dendritic cells for anomaly detection. In Proc. of the Congress on Evolutionary Computation (CEC), pp.664-671.
11. Y. Al-Hammadi, U. Aickelin, and J. Greensmith. (2008), DCA for detecting bots. In to appear in Proc. of the Congress on Evolutionary Computation (CEC)..
12. Jungwon Kim, Peter Bentley, and Christian Wallenta, (2006), "Danger Is Ubiquitous: Detecting Malicous Activities in Sensor Networks Using the Dendritic Cell Algorithm", ICARIS, LNCS 4163, pp. 390-403.
13. N. Lay and I. Bate. (2008)Improving the reliability of real time embedded systems using innate immune techniques. Evolutionary Intelligence: Special Issue on Artificial Immune Systems.
14. R. Oates, J. Greensmith, U. Aickelin, J. Garibaldi, and G. Kendall. (2007), The application of a dendritic cell algorithm to a robotic classifier. In Proc. of the 6th International Conference on Artificial Immune Systems (ICARIS), LNCS 4628,pp.204-215.
15. R. Coico, G. Sunshine, and E. Benjamini. (2003), Immunology: A Short Course. Wiley-Liss.
16. J. Greensmith, J. Twy cross, and U. Aickelin, (2006), "Dendritic cells for anomaly detection", In IEEE Congress on Evolutionary Computation (CEC 2006), PP. 664-671.
17. R. De Lemos, J. Timmis, S. Forrest and M. Ayara, (2007), "Immune Inspired Adaptable Error Detection for Automated Teller Machines", IEEE SMC Part C: Applications and Reviews. 37(5). Pp. 873-886.
18. Emilie Lundin, Hakan Kvarnstr "om and Erland Jonsson. A synthetic fraud data generation methodology. (2002), In Proceedings of the Fourth International Conference on Information and Communications Security (ICICS 2002), Singapore, December 9-12, 2002. Volume 2513 of Lecture Notes in Computer Science, Springer-Verlag.
19. Z. Ji and D. Dasgupta (2006). Applicability Issues of the Real-Valued Negative Selecion Algorithms. In Genetic and Evolutionary Computation Conference (GECCO), pp. 111-118.