Tracing the P2P Botnets Behaviours via Hybrid Analysis Approach
P2P botnets has become central issue that threatens global network security. The unification of botnets and P2P technology make it more powerful and complicated to detect. P2P botnets generally known with abnormal traffic behaviours may highly impact the networks operation, network security and caus...
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my.utem.eprints.135252015-05-28T04:32:24Z http://eprints.utem.edu.my/id/eprint/13525/ Tracing the P2P Botnets Behaviours via Hybrid Analysis Approach Raihana Syahirah Abdullah, RS Abdullah Mohd Faizal ABdollah, Faizal M.A. Zul Azri Muhamad Noh, ZAM Noh QA75 Electronic computers. Computer science P2P botnets has become central issue that threatens global network security. The unification of botnets and P2P technology make it more powerful and complicated to detect. P2P botnets generally known with abnormal traffic behaviours may highly impact the networks operation, network security and cause financial losses. In order to detect these P2P botnets, a highly-profile investigation on flow analysis is necessary. We consider hybrid analysis approach that integrate both static analysis and dynamic analysis approach. The hybrid analysis will be used in profiling the P2P behaviours and characteristics. Then, the findings of analysis results will contributes on P2P botnets behaviour pattern that will be used in constructing the general model of P2P botnets behaviour. Through the findings, this paper proposes a general P2P botnets behaviour model. The proposed model will be beneficial to further work on P2P botnets detection techniques. eurojournals 2014-01 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/13525/1/EJSR_118_1_09.pdf Raihana Syahirah Abdullah, RS Abdullah and Mohd Faizal ABdollah, Faizal M.A. and Zul Azri Muhamad Noh, ZAM Noh (2014) Tracing the P2P Botnets Behaviours via Hybrid Analysis Approach. European Journal of Scientific Research. pp. 75-85. ISSN 1450-216X/ 1450-202X |
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QA75 Electronic computers. Computer science Raihana Syahirah Abdullah, RS Abdullah Mohd Faizal ABdollah, Faizal M.A. Zul Azri Muhamad Noh, ZAM Noh Tracing the P2P Botnets Behaviours via Hybrid Analysis Approach |
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P2P botnets has become central issue that threatens global network security. The unification of botnets and P2P technology make it more powerful and complicated to detect. P2P botnets generally known with abnormal traffic behaviours may highly impact the networks operation, network security and cause financial losses. In order to detect these P2P botnets, a highly-profile investigation on flow analysis is necessary. We consider hybrid analysis approach that integrate both static analysis and dynamic analysis approach. The hybrid analysis will be used in profiling the P2P behaviours and characteristics. Then, the findings of analysis results will contributes on P2P botnets behaviour pattern that will be used in constructing the general model of P2P botnets behaviour. Through the findings, this paper proposes a general P2P botnets behaviour model. The proposed model will be beneficial to further work on P2P botnets detection techniques. |
format |
Article |
author |
Raihana Syahirah Abdullah, RS Abdullah Mohd Faizal ABdollah, Faizal M.A. Zul Azri Muhamad Noh, ZAM Noh |
author_facet |
Raihana Syahirah Abdullah, RS Abdullah Mohd Faizal ABdollah, Faizal M.A. Zul Azri Muhamad Noh, ZAM Noh |
author_sort |
Raihana Syahirah Abdullah, RS Abdullah |
title |
Tracing the P2P Botnets Behaviours via
Hybrid Analysis Approach
|
title_short |
Tracing the P2P Botnets Behaviours via
Hybrid Analysis Approach
|
title_full |
Tracing the P2P Botnets Behaviours via
Hybrid Analysis Approach
|
title_fullStr |
Tracing the P2P Botnets Behaviours via
Hybrid Analysis Approach
|
title_full_unstemmed |
Tracing the P2P Botnets Behaviours via
Hybrid Analysis Approach
|
title_sort |
tracing the p2p botnets behaviours via
hybrid analysis approach |
publisher |
eurojournals |
publishDate |
2014 |
url |
http://eprints.utem.edu.my/id/eprint/13525/1/EJSR_118_1_09.pdf http://eprints.utem.edu.my/id/eprint/13525/ |
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1665905548474712064 |
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13.211869 |