Integrating real-time analysis with the dendritic cell algorithm through segmentation
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 ana...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
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2009
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| Online Access: | https://eprints.nottingham.ac.uk/34134/ |
| _version_ | 1848794781187047424 |
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| author | Gu, Feng Greensmith, Julie Aickelin, Uwe |
| author_facet | Gu, Feng Greensmith, Julie Aickelin, Uwe |
| author_sort | Gu, Feng |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T19:21:39Z |
| format | Conference or Workshop Item |
| id | nottingham-34134 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:21:39Z |
| publishDate | 2009 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-341342020-05-04T16:28:05Z https://eprints.nottingham.ac.uk/34134/ Integrating real-time analysis with the dendritic cell algorithm through segmentation Gu, Feng Greensmith, Julie Aickelin, Uwe 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. 2009-01-01 Conference or Workshop Item PeerReviewed Gu, Feng, Greensmith, Julie and Aickelin, Uwe (2009) Integrating real-time analysis with the dendritic cell algorithm through segmentation. In: GECCO '09: Proceedings of the 11th Genetic and Evolutionary Computation Conference, 8-12 July 2009, Montreal, Canada. Dendritic Cell Algorithm Intrusion Detection Systems Real-Time Analysis Segmentation http://dl.acm.org/citation.cfm?id=1570063&CFID=802004103&CFTOKEN=27246016 |
| spellingShingle | Dendritic Cell Algorithm Intrusion Detection Systems Real-Time Analysis Segmentation Gu, Feng Greensmith, Julie Aickelin, Uwe Integrating real-time analysis with the dendritic cell algorithm through segmentation |
| title | Integrating real-time analysis with the dendritic cell algorithm through segmentation |
| title_full | Integrating real-time analysis with the dendritic cell algorithm through segmentation |
| title_fullStr | Integrating real-time analysis with the dendritic cell algorithm through segmentation |
| title_full_unstemmed | Integrating real-time analysis with the dendritic cell algorithm through segmentation |
| title_short | Integrating real-time analysis with the dendritic cell algorithm through segmentation |
| title_sort | integrating real-time analysis with the dendritic cell algorithm through segmentation |
| topic | Dendritic Cell Algorithm Intrusion Detection Systems Real-Time Analysis Segmentation |
| url | https://eprints.nottingham.ac.uk/34134/ https://eprints.nottingham.ac.uk/34134/ |