Dendritic Cells for Anomaly Detection

8 Pages Posted: 11 Jul 2017

See all articles by Julie Greensmith

Julie Greensmith

University of Nottingham - School of Computer Science

Jamie Twycross

University of Nottingham - School of Computer Science

Uwe Aickelin

University of Melbourne - School of Computing and Information Systems

Date Written: January 1, 2006

Abstract

Artificial immune systems, more specifically the negative selection algorithm, have previously been applied to intrusion detection. The aim of this research is to develop an intrusion detection system based on a novel concept in immunology, the Danger Theory. Dendritic Cells (DCs) are antigen presenting cells and key to the activation of the human immune system. DCs perform the vital role of combining signals from the host tissue and correlate these signals with proteins known as antigens. In algorithmic terms, individual DCs perform multi-sensor data fusion based on time-windows. The whole population of DCs asynchronously correlates the fused signals with a secondary data stream. The behaviour of human DCs is abstracted to form the DC Algorithm (DCA), which is implemented using an immune inspired framework, libtissue. This system is used to detect context switching for a basic machine learning dataset and to detect outgoing portscans in real-time. Experimental results show a significant difference between an outgoing portscan and normal traffic.

Suggested Citation

Greensmith, Julie and Twycross, Jamie and Aickelin, Uwe, Dendritic Cells for Anomaly Detection (January 1, 2006). Available at SSRN: https://ssrn.com/abstract=2831377 or http://dx.doi.org/10.2139/ssrn.2831377

Julie Greensmith

University of Nottingham - School of Computer Science ( email )

Jubilee Campus
Wollaton Road
Nottingham, NG8 1BB
United Kingdom

Jamie Twycross

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
27
Abstract Views
308
PlumX Metrics