Exploration Of The Dendritic Cell Algorithm Using The Duration Calculus

TL;DR

This paper employs Duration Calculus to formally analyze the Dendritic Cell Algorithm, revealing its potential for real-time anomaly detection and suggesting modifications to enhance its real-time capabilities.

Contribution

It introduces a formal Duration Calculus-based specification of the DCA, demonstrating its real-time potential and proposing a real-time analysis component for improvement.

Findings

Individual cells can perform real-time detection

Standard DCA analysis constrains real-time capability

Replaced analysis with periodic real-time component enhances performance

Abstract

As one of the newest members in Artificial Immune Systems (AIS), the Dendritic Cell Algorithm (DCA) has been applied to a range of problems. These applications mainly belong to the field of anomaly detection. However, real-time detection, a new challenge to anomaly detection, requires improvement on the real-time capability of the DCA. To assess such capability, formal methods in the research of rea-time systems can be employed. The findings of the assessment can provide guideline for the future development of the algorithm. Therefore, in this paper we use an interval logic based method, named the Duration Calculus (DC), to specify a simplified single-cell model of the DCA. Based on the DC specifications with further induction, we find that each individual cell in the DCA can perform its function as a detector in real-time. Since the DCA can be seen as many such cells operating in parallel, it is potentially capable of performing real-time detection. However, the analysis process of the standard DCA constricts its real-time capability. As a result, we conclude that the analysis process of the standard DCA should be replaced by a real-time analysis component, which can perform periodic analysis for the purpose of real-time detection.