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As an immune inspired algorithm, the Dendritic Cell Algorithm (DCA) has beenapplied to a range of problems, particularly in the area of intrusiondetection. Ideally, the intrusion detection should be performed in real-time,to continuously detect misuses as soon as they occur. Consequently, theanalysis process performed by an intrusion detection system must operate inreal-time or near-to real-time. The analysis process of the DCA is currentlyperformed offline, therefore to improve the algorithm's performance we suggestthe development of a real-time analysis component. The initial step of thedevelopment is to apply segmentation to the DCA. This involves segmenting thecurrent output of the DCA into slices and performing the analysis in variousways. Two segmentation approaches are introduced and tested in this paper,namely antigen based segmentation (ABS) and time based segmentation (TBS). Theresults of the corresponding experiments suggest that applying segmentationproduces different and significantly better results in some cases, whencompared to the standard DCA without segmentation. Therefore, we conclude thatthe segmentation is applicable to the DCA for the purpose of real-timeanalysis.

Integrating Real-Time Analysis With The Dendritic Cell Algorithm Through Segmentation