A multi-attribute decision model for intrusion response system
The objective of this paper is to present a multi-attribute decision model for network intrusion response. The proposed technique uses a weighted linear combination (WLC) model to standardize the different attributes to a common numeric range before applying a genetic algorithm to determine the appr...
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2014
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um-106882014-06-25T06:47:02Z A multi-attribute decision model for intrusion response system Fessi, B.A. Benabdallah, S. Boudriga, N. Hamdi, M. TJ Mechanical engineering and machinery The objective of this paper is to present a multi-attribute decision model for network intrusion response. The proposed technique uses a weighted linear combination (WLC) model to standardize the different attributes to a common numeric range before applying a genetic algorithm to determine the appropriate alternative. The model is characterized by a new implementation of individual structure based on the response-resource matrix and a fitness function based on cost-benefit approach. The decision model parameters are represented by vectors modeling the different attributes that are respectively: financial cost, reputation loss, and processing resources. The paper presents a new approach for handling a multi-attribute decision problem in intrusion response context which has not been addressed in previous studies. Finally, this paper will discuss the findings of simulation experiments and will conclude by discussing the effectiveness of the proposed approach. © 2014 Elsevier Inc. All rights reserved. Elsevier Inc. 2014 Article PeerReviewed http://www.scopus.com/inward/record.url?eid=2-s2.0-84898541002&partnerID=40&md5=d8751539993aaaede6ab46c16eeecc77 Fessi, B.A.; Benabdallah, S.; Boudriga, N.; Hamdi, M. (2014) A multi-attribute decision model for intrusion response system. Information Sciences <http://eprints.um.edu.my/view/publication/Information_Sciences.html>, 270. pp. 237-254. ISSN 00200255 http://eprints.um.edu.my/10688/ |
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University Malaya |
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TJ Mechanical engineering and machinery |
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TJ Mechanical engineering and machinery Fessi, B.A. Benabdallah, S. Boudriga, N. Hamdi, M. A multi-attribute decision model for intrusion response system |
description |
The objective of this paper is to present a multi-attribute decision model for network intrusion response. The proposed technique uses a weighted linear combination (WLC) model to standardize the different attributes to a common numeric range before applying a genetic algorithm to determine the appropriate alternative. The model is characterized by a new implementation of individual structure based on the response-resource matrix and a fitness function based on cost-benefit approach. The decision model parameters are represented by vectors modeling the different attributes that are respectively: financial cost, reputation loss, and processing resources. The paper presents a new approach for handling a multi-attribute decision problem in intrusion response context which has not been addressed in previous studies. Finally, this paper will discuss the findings of simulation experiments and will conclude by discussing the effectiveness of the proposed approach. © 2014 Elsevier Inc. All rights reserved. |
format |
Article |
author |
Fessi, B.A. Benabdallah, S. Boudriga, N. Hamdi, M. |
author_facet |
Fessi, B.A. Benabdallah, S. Boudriga, N. Hamdi, M. |
author_sort |
Fessi, B.A. |
title |
A multi-attribute decision model for intrusion response system |
title_short |
A multi-attribute decision model for intrusion response system |
title_full |
A multi-attribute decision model for intrusion response system |
title_fullStr |
A multi-attribute decision model for intrusion response system |
title_full_unstemmed |
A multi-attribute decision model for intrusion response system |
title_sort |
multi-attribute decision model for intrusion response system |
publisher |
Elsevier Inc. |
publishDate |
2014 |
url |
http://www.scopus.com/inward/record.url?eid=2-s2.0-84898541002&partnerID=40&md5=d8751539993aaaede6ab46c16eeecc77 http://www.scopus.com/inward/record.url?eid=2-s2.0-84898541002&partnerID=40&md5=d8751539993aaaede6ab46c16eeecc77 |
first_indexed |
2018-09-06T05:52:21Z |
last_indexed |
2018-09-06T05:52:21Z |
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1610836231278559232 |