Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm

TL;DR

This paper introduces a biologically inspired Dendritic Cell Algorithm that models immune system signal processing to improve anomaly detection, demonstrated effectively on port scan detection tasks.

Contribution

It presents a novel algorithm based on dendritic cell functions, integrating biological immune mechanisms into anomaly detection systems.

Findings

Successfully detects port scans using the Dendritic Cell Algorithm

Demonstrates the effectiveness of immune-inspired information fusion

Provides detailed algorithmic and experimental insights

Abstract

Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system, providing the initial detection of pathogenic invaders. Research into this family of cells has revealed that they perform information fusion which directs immune responses. We have derived a Dendritic Cell Algorithm based on the functionality of these cells, by modelling the biological signals and differentiation pathways to build a control mechanism for an artificial immune system. We present algorithmic details in addition to experimental results, when the algorithm was applied to anomaly detection for the detection of port scans. The results show the Dendritic Cell Algorithm is sucessful at detecting port scans.