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Data analysis technique to extract threshold value for Fuzzy Inference System in classifying malicious agents

This paper describes a data analysis technique used to extract threshold values of a Fuzzy Inference System's (FIS) inputs. In this work, the FIS is used to classify malicious agents' behaviour in a Multi-Agent System (MAS) environment. The extraction of suitable FIS inputs threshold value...

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Main Authors: Musa, N.A., Yusoff, M.Z.M., Yusoff, Y., Ismail, R.
Format: Conference Paper
Language:English
Published: 2017
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spelling my.uniten.dspace-56242017-11-21T07:49:28Z Data analysis technique to extract threshold value for Fuzzy Inference System in classifying malicious agents Musa, N.A. Yusoff, M.Z.M. Yusoff, Y. Ismail, R. This paper describes a data analysis technique used to extract threshold values of a Fuzzy Inference System's (FIS) inputs. In this work, the FIS is used to classify malicious agents' behaviour in a Multi-Agent System (MAS) environment. The extraction of suitable FIS inputs threshold values in the MAS environment are based on data analysis derived from several simulation runs. Subsequently, the extracted threshold values are applied in the rules of the FIS framework for classifying malicious agents' behaviors. Results indicated that extracting the fuzzy threshold values using the data analysis technique is an acceptable alternative method when no domain expert is available. © 2014 IEEE. 2017-11-21T04:08:39Z 2017-11-21T04:08:39Z 2015 Conference Paper 10.1109/ICIMU.2014.7066601 en Conference Proceedings - 6th International Conference on Information Technology and Multimedia at UNITEN: Cultivating Creativity and Enabling Technology Through the Internet of Things, ICIMU 2014 23 March 2015, Article number 7066601, Pages 44-48
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
description This paper describes a data analysis technique used to extract threshold values of a Fuzzy Inference System's (FIS) inputs. In this work, the FIS is used to classify malicious agents' behaviour in a Multi-Agent System (MAS) environment. The extraction of suitable FIS inputs threshold values in the MAS environment are based on data analysis derived from several simulation runs. Subsequently, the extracted threshold values are applied in the rules of the FIS framework for classifying malicious agents' behaviors. Results indicated that extracting the fuzzy threshold values using the data analysis technique is an acceptable alternative method when no domain expert is available. © 2014 IEEE.
format Conference Paper
author Musa, N.A.
Yusoff, M.Z.M.
Yusoff, Y.
Ismail, R.
spellingShingle Musa, N.A.
Yusoff, M.Z.M.
Yusoff, Y.
Ismail, R.
Data analysis technique to extract threshold value for Fuzzy Inference System in classifying malicious agents
author_facet Musa, N.A.
Yusoff, M.Z.M.
Yusoff, Y.
Ismail, R.
author_sort Musa, N.A.
title Data analysis technique to extract threshold value for Fuzzy Inference System in classifying malicious agents
title_short Data analysis technique to extract threshold value for Fuzzy Inference System in classifying malicious agents
title_full Data analysis technique to extract threshold value for Fuzzy Inference System in classifying malicious agents
title_fullStr Data analysis technique to extract threshold value for Fuzzy Inference System in classifying malicious agents
title_full_unstemmed Data analysis technique to extract threshold value for Fuzzy Inference System in classifying malicious agents
title_sort data analysis technique to extract threshold value for fuzzy inference system in classifying malicious agents
publishDate 2017
_version_ 1644493736702377984
score 13.160551

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