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