Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows

As an immune-inspired algorithm, the Dendritic Cell Algorithm (DCA), produces promising performance in the field of anomaly detection. This paper presents the application of the DCA to a standard data set, the KDD 99 data set. The results of different implementation versions of the DCA, including an...

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Main Authors: Gu, Feng, Greensmith, Julie, Aickelin, Uwe
Other Authors: Bentley, Peter
Format: Book Section
Published: Springer 2008
Online Access:https://eprints.nottingham.ac.uk/989/
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author Gu, Feng
Greensmith, Julie
Aickelin, Uwe
author2 Bentley, Peter
author_facet Bentley, Peter
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), produces promising performance in the field of anomaly detection. This paper presents the application of the DCA to a standard data set, the KDD 99 data set. The results of different implementation versions of the DCA, including antigen multiplier and moving time windows, are reported. The real-valued Negative Selection Algorithm (NSA) using constant-sized detectors and the C4.5 decision tree algorithm are used, to conduct a baseline comparison. The results suggest that the DCA is applicable to KDD 99 data set, and the antigen multiplier and moving time windows have the same effect on the DCA for this particular data set. The real-valued NSA with contant-sized detectors is not applicable to the data set. And the C4.5 decision tree algorithm provides a benchmark of the classification performance for this data set.
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spelling nottingham-9892020-05-04T20:27:45Z https://eprints.nottingham.ac.uk/989/ Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows Gu, Feng Greensmith, Julie Aickelin, Uwe As an immune-inspired algorithm, the Dendritic Cell Algorithm (DCA), produces promising performance in the field of anomaly detection. This paper presents the application of the DCA to a standard data set, the KDD 99 data set. The results of different implementation versions of the DCA, including antigen multiplier and moving time windows, are reported. The real-valued Negative Selection Algorithm (NSA) using constant-sized detectors and the C4.5 decision tree algorithm are used, to conduct a baseline comparison. The results suggest that the DCA is applicable to KDD 99 data set, and the antigen multiplier and moving time windows have the same effect on the DCA for this particular data set. The real-valued NSA with contant-sized detectors is not applicable to the data set. And the C4.5 decision tree algorithm provides a benchmark of the classification performance for this data set. Springer Bentley, Peter Lee, Doheon Jung, Sungwon 2008 Book Section PeerReviewed Gu, Feng, Greensmith, Julie and Aickelin, Uwe (2008) Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows. In: Artificial immune systems: 7th international conference, ICARIS 2008, Phuket, Thailand, August 10-13, 2008: proceedings. Lecture notes in computer science (5132). Springer, pp. 142-153. ISBN 9783540850717 http://biosoft.kaist.ac.kr/icaris2008/
spellingShingle Gu, Feng
Greensmith, Julie
Aickelin, Uwe
Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows
title Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows
title_full Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows
title_fullStr Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows
title_full_unstemmed Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows
title_short Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows
title_sort further exploration of the dendritic cell algorithm: antigen multiplier and time windows
url https://eprints.nottingham.ac.uk/989/
https://eprints.nottingham.ac.uk/989/