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An adaptive anomaly threshold in artificial dendrite cell algorithm

The dendrite cell algorithm (DCA) relies on the multi-context antigen value (MCAV) to determine the abnormality of a record by comparing it with anomaly threshold.In practice, the threshold is pre-determined before mining based on previous information and the existing MCAV is inefficient when expos...

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Main Authors: Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak
Format: Conference or Workshop Item
Language:English
Published: 2017
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://repo.uum.edu.my/22836/1/ICOCI%202017%20250-255.pdf
http://repo.uum.edu.my/22836/
http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap04e/PID124-250-255e.pdf
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spelling my.uum.repo.228362017-07-27T01:09:42Z http://repo.uum.edu.my/22836/ An adaptive anomaly threshold in artificial dendrite cell algorithm Mohamad Mohsin, Mohamad Farhan Abu Bakar, Azuraliza Hamdan, Abdul Razak QA75 Electronic computers. Computer science The dendrite cell algorithm (DCA) relies on the multi-context antigen value (MCAV) to determine the abnormality of a record by comparing it with anomaly threshold.In practice, the threshold is pre-determined before mining based on previous information and the existing MCAV is inefficient when expose to extreme values.This causes the DCA fails to detect unlabeled data if the new pattern distinct from previous information and reduces the detection accuracy.This paper proposed an adaptive anomaly threshold for DCA using the statistical cumulative sum (CUSUM) with the aim to improve its detection capability.In the proposed approach, the MCAV were normalized with upper CUSUM and the new anomaly threshold was calculated during run time by considering the acceptance value and min MCAV.From the experiments towards 12 datasets, the new version of DCA generated a better detection result than its previous version in term of sensitivity, specificity, false detection rate, and accuracy. 2017-04-25 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/22836/1/ICOCI%202017%20250-255.pdf Mohamad Mohsin, Mohamad Farhan and Abu Bakar, Azuraliza and Hamdan, Abdul Razak (2017) An adaptive anomaly threshold in artificial dendrite cell algorithm. In: 6th International Conference on Computing & Informatics (ICOCI2017), 25 - 27 April 2017, Kuala Lumpur. http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap04e/PID124-250-255e.pdf
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Mohamad Mohsin, Mohamad Farhan
Abu Bakar, Azuraliza
Hamdan, Abdul Razak
An adaptive anomaly threshold in artificial dendrite cell algorithm
description The dendrite cell algorithm (DCA) relies on the multi-context antigen value (MCAV) to determine the abnormality of a record by comparing it with anomaly threshold.In practice, the threshold is pre-determined before mining based on previous information and the existing MCAV is inefficient when expose to extreme values.This causes the DCA fails to detect unlabeled data if the new pattern distinct from previous information and reduces the detection accuracy.This paper proposed an adaptive anomaly threshold for DCA using the statistical cumulative sum (CUSUM) with the aim to improve its detection capability.In the proposed approach, the MCAV were normalized with upper CUSUM and the new anomaly threshold was calculated during run time by considering the acceptance value and min MCAV.From the experiments towards 12 datasets, the new version of DCA generated a better detection result than its previous version in term of sensitivity, specificity, false detection rate, and accuracy.
format Conference or Workshop Item
author Mohamad Mohsin, Mohamad Farhan
Abu Bakar, Azuraliza
Hamdan, Abdul Razak
author_facet Mohamad Mohsin, Mohamad Farhan
Abu Bakar, Azuraliza
Hamdan, Abdul Razak
author_sort Mohamad Mohsin, Mohamad Farhan
title An adaptive anomaly threshold in artificial dendrite cell algorithm
title_short An adaptive anomaly threshold in artificial dendrite cell algorithm
title_full An adaptive anomaly threshold in artificial dendrite cell algorithm
title_fullStr An adaptive anomaly threshold in artificial dendrite cell algorithm
title_full_unstemmed An adaptive anomaly threshold in artificial dendrite cell algorithm
title_sort adaptive anomaly threshold in artificial dendrite cell algorithm
publishDate 2017
url http://repo.uum.edu.my/22836/1/ICOCI%202017%20250-255.pdf
http://repo.uum.edu.my/22836/
http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap04e/PID124-250-255e.pdf
_version_ 1644283630321664000
score 13.211869

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