Information Fusion in the Immune System

TL;DR

This paper reviews biologically-inspired information fusion methods based on the human immune system, highlighting their application in real-time intrusion detection and summarizing their mechanisms and implementations.

Contribution

It provides a comprehensive overview of biological immune system mechanisms for information fusion and their implementation as Artificial Immune Systems for cybersecurity.

Findings

AISs effectively detect real-time computer intrusions

Biological immune mechanisms can be adapted for information fusion

AISs leverage multi-level data sources for improved performance

Abstract

Biologically-inspired methods such as evolutionary algorithms and neural networks are proving useful in the field of information fusion. Artificial Immune Systems (AISs) are a biologically-inspired approach which take inspiration from the biological immune system. Interestingly, recent research has show how AISs which use multi-level information sources as input data can be used to build effective algorithms for real time computer intrusion detection. This research is based on biological information fusion mechanisms used by the human immune system and as such might be of interest to the information fusion community. The aim of this paper is to present a summary of some of the biological information fusion mechanisms seen in the human immune system, and of how these mechanisms have been implemented as AISs