The Deterministic Dendritic Cell Algorithm

12 Pages Posted: 10 Sep 2016

See all articles by Julie Greensmith

Julie Greensmith

University of Nottingham - School of Computer Science

Uwe Aickelin

University of Melbourne - School of Computing and Information Systems

Date Written: January 1, 2008

Abstract

The Dendritic Cell Algorithm is an immune-inspired algorithm originally based on the function of natural dendritic cells. The original instantiation of the algorithm is a highly stochastic algorithm. While the performance of the algorithm is good when applied to large real-time datasets, it is difficult to analyse due to the number of random-based elements. In this paper a deterministic version of the algorithm is proposed, implemented and tested using a port scan dataset to provide a controllable system. This version consists of a controllable amount of parameters, which are experimented with in this paper. In addition the effects are examined of the use of time windows and variation on the number of cells, both which are shown to influence the algorithm. Finally a novel metric for the assessment of the algorithms output is introduced and proves to be a more sensitive metric than the metric used with the original Dendritic Cell Algorithm.

Suggested Citation

Greensmith, Julie and Aickelin, Uwe, The Deterministic Dendritic Cell Algorithm (January 1, 2008). Available at SSRN: https://ssrn.com/abstract=2831280 or http://dx.doi.org/10.2139/ssrn.2831280

Julie Greensmith

University of Nottingham - School of Computer Science ( email )

Jubilee Campus
Wollaton Road
Nottingham, NG8 1BB
United Kingdom

Uwe Aickelin (Contact Author)

University of Melbourne - School of Computing and Information Systems ( email )

Australia

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
45
Abstract Views
335
PlumX Metrics