The dendritic cell algorithm for intrusion detection

Gu, Feng; Greensmith, Julie; Aickelin, Uwe

Abstract

As one of the solutions to intrusion detection problems, Artificial Immune Systems (AIS) have shown their advantages. Unlike genetic algorithms, there is no one archetypal AIS, instead there are four major paradigms. Among them, the Dendritic Cell Algorithm (DCA) has produced promising results in various applications. The aim of this chapter is to demonstrate the potential for the DCA as a suitable candidate for intrusion detection problems. We review some of the commonly used AIS paradigms for intrusion detection problems and demonstrate the advantages of one particular algorithm, the DCA. In order to clearly describe the algorithm, the background to its development and a formal definition are given. In addition, improvements to the original DCA are presented and their implications are discussed, including previous work done on an online analysis component with segmentation and ongoing work on automated data pre-processing. Based on preliminary results, both improvements appear to be promising for online anomaly-based intrusion detection.

Citation

Gu, F., Greensmith, J., & Aickelin, U. (2012). The dendritic cell algorithm for intrusion detection. In P. Lio, & D. Verma (Eds.), Biologically inspired networking and sensing : algorithms and architectures. IGI Global

• Acceptance Date: Jan 11, 2011
• Publication Date: Mar 30, 2012
• Deposit Date: Jun 17, 2016
• Publicly Available Date: Jun 17, 2016
• Publisher: IGI Global
• Peer Reviewed: Peer Reviewed
• Book Title: Biologically inspired networking and sensing : algorithms and architectures
• ISBN: 9781613500927
• Public URL: https://nottingham-repository.worktribe.com/output/709610
• Publisher URL: http://www.igi-global.com/book/biologically-inspired-networking-sensing/51948
• Related Public URLs: http://ima.ac.uk/papers/gu2011.pdf
• Contract Date: Jun 17, 2016