Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection
Network and information security are regarded as some of the most pressing problems of contemporary economy, affecting both individual citizens and entire societies, making them a highlight for homeland security. Innovative approaches to handle this challenge are undertaken by the scientific communi...
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Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2019/5826737 |
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doaj-01069edca4394ce09740bd4d771805422020-11-25T02:14:51ZengHindawi-WileyComplexity1076-27871099-05262019-01-01201910.1155/2019/58267375826737Practical Employment of Granular Computing to Complex Application Layer Cyberattack DetectionRafał Kozik0Marek Pawlicki1Michał Choraś2Witold Pedrycz3Institute of Telecommunications and Computer Science, UTP University of Science and Technology, Bydgoszcz, PolandInstitute of Telecommunications and Computer Science, UTP University of Science and Technology, Bydgoszcz, PolandInstitute of Telecommunications and Computer Science, UTP University of Science and Technology, Bydgoszcz, PolandDepartment Electrical and Computer Engineering, University of Alberta, CanadaNetwork and information security are regarded as some of the most pressing problems of contemporary economy, affecting both individual citizens and entire societies, making them a highlight for homeland security. Innovative approaches to handle this challenge are undertaken by the scientific community, proposing the utilization of the emerging, advanced machine learning methods. This very paper puts forward a novel approach to the detection of cyberattacks taking inventory of the practical application of information granules. The feasibility of utilizing Granular Computing (GC) as a solution to the most current challenges in cybersecurity is researched. To the best of our knowledge, granular computing has not yet been widely examined or used for cybersecurity application purposes. The major contribution of this work is a method for constructing information granules from network data. We then report promising results on a benchmark dataset.http://dx.doi.org/10.1155/2019/5826737 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rafał Kozik Marek Pawlicki Michał Choraś Witold Pedrycz |
spellingShingle |
Rafał Kozik Marek Pawlicki Michał Choraś Witold Pedrycz Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection Complexity |
author_facet |
Rafał Kozik Marek Pawlicki Michał Choraś Witold Pedrycz |
author_sort |
Rafał Kozik |
title |
Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection |
title_short |
Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection |
title_full |
Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection |
title_fullStr |
Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection |
title_full_unstemmed |
Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection |
title_sort |
practical employment of granular computing to complex application layer cyberattack detection |
publisher |
Hindawi-Wiley |
series |
Complexity |
issn |
1076-2787 1099-0526 |
publishDate |
2019-01-01 |
description |
Network and information security are regarded as some of the most pressing problems of contemporary economy, affecting both individual citizens and entire societies, making them a highlight for homeland security. Innovative approaches to handle this challenge are undertaken by the scientific community, proposing the utilization of the emerging, advanced machine learning methods. This very paper puts forward a novel approach to the detection of cyberattacks taking inventory of the practical application of information granules. The feasibility of utilizing Granular Computing (GC) as a solution to the most current challenges in cybersecurity is researched. To the best of our knowledge, granular computing has not yet been widely examined or used for cybersecurity application purposes. The major contribution of this work is a method for constructing information granules from network data. We then report promising results on a benchmark dataset. |
url |
http://dx.doi.org/10.1155/2019/5826737 |
work_keys_str_mv |
AT rafałkozik practicalemploymentofgranularcomputingtocomplexapplicationlayercyberattackdetection AT marekpawlicki practicalemploymentofgranularcomputingtocomplexapplicationlayercyberattackdetection AT michałchoras practicalemploymentofgranularcomputingtocomplexapplicationlayercyberattackdetection AT witoldpedrycz practicalemploymentofgranularcomputingtocomplexapplicationlayercyberattackdetection |
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1724899291543109632 |