Introducing Dendritic Cells as a Novel Immune-Inspired Algorithm for Anomoly Detection

TL;DR

This paper introduces a novel anomaly detection algorithm inspired by dendritic cells in the immune system, leveraging their role in immune response coordination to improve detection capabilities.

Contribution

The authors developed an immune-inspired algorithm based on dendritic cell functions, integrating signals and differentiation pathways for anomaly detection.

Findings

Preliminary results show effective anomaly detection performance.

The algorithm mimics immune system processes for improved robustness.

Potential for integration into large distributed immune systems.

Abstract

Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system. Research into this family of cells has revealed that they perform the role of coordinating T-cell based immune responses, both reactive and for generating tolerance. We have derived an algorithm based on the functionality of these cells, and have used the signals and differentiation pathways to build a control mechanism for an artificial immune system. We present our algorithmic details in addition to some preliminary results, where the algorithm was applied for the purpose of anomaly detection. We hope that this algorithm will eventually become the key component within a large, distributed immune system, based on sound immunological concepts.