Sensing Danger: Innate Immunology for Intrusion Detection

TL;DR

This paper introduces two novel immune-inspired algorithms for intrusion detection, leveraging recent immunological discoveries like Dendritic Cells, and demonstrates their effectiveness on real-world security challenges.

Contribution

The paper presents new algorithms based on modern immunology, improving upon previous models and applying them successfully to practical intrusion detection problems.

Findings

Algorithms show promising results on real-world intrusion detection tasks.

Modern immunological insights enhance the effectiveness of artificial immune systems.

Next-generation immune algorithms have a bright future in security applications.

Abstract

The immune system provides an ideal metaphor for anomaly detection in general and computer security in particular. Based on this idea, artificial immune systems have been used for a number of years for intrusion detection, unfortunately so far with little success. However, these previous systems were largely based on immunological theory from the 1970s and 1980s and over the last decade our understanding of immunological processes has vastly improved. In this paper we present two new immune inspired algorithms based on the latest immunological discoveries, such as the behaviour of Dendritic Cells. The resultant algorithms are applied to real world intrusion problems and show encouraging results. Overall, we believe there is a bright future for these next generation artificial immune algorithms.