Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows

Gu, Feng; Greensmith, Julie; Aickelin, Uwe

Abstract

As an immune-inspired algorithm, the Dendritic Cell Algorithm (DCA), produces promising performance in the field of anomaly detection. This paper presents the application of the DCA to a standard data set, the KDD 99 data set. The results of different implementation versions of the DCA, including antigen multiplier and moving time windows, are reported. The real-valued Negative Selection Algorithm (NSA) using constant-sized detectors and the C4.5 decision tree algorithm are used, to conduct a baseline comparison. The results suggest that the DCA is applicable to KDD 99 data set, and the antigen multiplier and moving time windows have the same effect on the DCA for this particular data set. The real-valued NSA with contant-sized detectors is not applicable to the data set. And the C4.5 decision tree algorithm provides a benchmark of the classification performance for this data set.

Citation

Gu, F., Greensmith, J., & Aickelin, U. (2008, August). Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows. Presented at 7th international conference, ICARIS 2008, Phuket, Thailand

• Presentation Conference Type: Edited Proceedings
• Conference Name: 7th international conference, ICARIS 2008
• Start Date: Aug 10, 2008
• End Date: Aug 13, 2008
• Publication Date: Jan 1, 2008
• Deposit Date: Jan 30, 2009
• Publicly Available Date: Jan 30, 2009
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Pages: 142–153
• Series Title: Lecture notes in computer science
• Series Number: 5132
• Series ISSN: 1611-3349
• Book Title: Artificial immune systems
• ISBN: 9783540850717
• DOI: https://doi.org/10.1007/978-3-540-85072-4_13
• Public URL: https://nottingham-repository.worktribe.com/output/1015828
• Publisher URL: https://link.springer.com/chapter/10.1007/978-3-540-85072-4_13