Conference Proceedings

Dendritic Cells for Anomaly Detection

Julie Greensmith, Jamie Twycross, Uwe Aickelin

Proceedings of the IEEE Congress on Evolutionary Computation (CEC2006) | IEEE | Published : 2006


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 behav..

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University of Melbourne Researchers


Awarded by EPSRC

Funding Acknowledgements

This project is supported by the EPSRC (GR/S47809/01), UWE, Hewlett Packard Labs, Bristol, and the Firestorm IDS team. Thanks to Jim Greensmith, Markus Hammonds and Dr Jon Timmis for their comments.