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Online peer-to-peer traffic identification based on complex events processing of traffic event signatures
Bassi, Joseph Stephen1, Loo, Hui Ru2, Ismahani Ismail3, Ban Mohammed Khammas4, Marsono, Muhammad Nadzir5.
Peer-to-Peer (P2P) applications are bandwidth-heavy and lead to network
congestion. The masquerading nature of P2P traffic makes conventional
methods of its identification futile. In order to manage and control P2P traffic
efficiently preferably in the network, it is necessary to identify such traffic online
and accurately. This paper proposes a technique for online P2P identification
based on traffic events signatures. The experimental results show that it is able
to identify P2P traffic on the fly with an accuracy of 97.7%, precision of 98% and
recall of 99.2%.
Affiliation:
- Universiti Teknologi Malaysia, Malaysia
- Universiti Teknologi Malaysia, Malaysia
- Universiti Teknologi Malaysia, Malaysia
- Universiti Teknologi Malaysia, Malaysia
- Universiti Teknologi Malaysia, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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