Towards Cost-Effective P2P Traffic Classification in Cloud Environment

Tao BAN; Shanqing GUO; Masashi ETO; Daisuke INOUE; Koji NAKAO

doi:10.1587/transinf.E95.D.2888

Towards Cost-Effective P2P Traffic Classification in Cloud Environment

Tao BAN, Shanqing GUO, Masashi ETO, Daisuke INOUE, Koji NAKAO

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Characterization of peer-to-peer (P2P) traffic is an essential step to develop workload models towards capacity planning and cyber-threat countermeasure over P2P networks. In this paper, we present a classification scheme for characterizing P2P file-sharing hosts based on transport layer statistical features. The proposed scheme is accessed on a virtualized environment that simulates a P2P-friendly cloud system. The system shows high accuracy in differentiating P2P file-sharing hosts from ordinary hosts. Its tunability regarding monitoring cost, system response time, and prediction accuracy is demonstrated by a series of experiments. Further study on feature selection is pursued to identify the most essential discriminators that contribute most to the classification. Experimental results show that an equally accurate system could be obtained using only 3 out of the 18 defined discriminators, which further reduces the monitoring cost and enhances the adaptability of the system.

Publication: IEICE TRANSACTIONS on Information Vol.E95-D No.12 pp.2888-2897

Publication Date: 2012/12/01

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Online ISSN: 1745-1361

DOI: 10.1587/transinf.E95.D.2888

Type of Manuscript: Special Section PAPER (Special Section on Parallel and Distributed Computing and Networking)

Category: Network and Communication

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Tao BAN, Shanqing GUO, Masashi ETO, Daisuke INOUE, Koji NAKAO, "Towards Cost-Effective P2P Traffic Classification in Cloud Environment" in IEICE TRANSACTIONS on Information, vol. E95-D, no. 12, pp. 2888-2897, December 2012, doi: 10.1587/transinf.E95.D.2888.
Abstract: Characterization of peer-to-peer (P2P) traffic is an essential step to develop workload models towards capacity planning and cyber-threat countermeasure over P2P networks. In this paper, we present a classification scheme for characterizing P2P file-sharing hosts based on transport layer statistical features. The proposed scheme is accessed on a virtualized environment that simulates a P2P-friendly cloud system. The system shows high accuracy in differentiating P2P file-sharing hosts from ordinary hosts. Its tunability regarding monitoring cost, system response time, and prediction accuracy is demonstrated by a series of experiments. Further study on feature selection is pursued to identify the most essential discriminators that contribute most to the classification. Experimental results show that an equally accurate system could be obtained using only 3 out of the 18 defined discriminators, which further reduces the monitoring cost and enhances the adaptability of the system.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.E95.D.2888/_p

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@ARTICLE{e95-d_12_2888,
author={Tao BAN, Shanqing GUO, Masashi ETO, Daisuke INOUE, Koji NAKAO, },
journal={IEICE TRANSACTIONS on Information},
title={Towards Cost-Effective P2P Traffic Classification in Cloud Environment},
year={2012},
volume={E95-D},
number={12},
pages={2888-2897},
abstract={Characterization of peer-to-peer (P2P) traffic is an essential step to develop workload models towards capacity planning and cyber-threat countermeasure over P2P networks. In this paper, we present a classification scheme for characterizing P2P file-sharing hosts based on transport layer statistical features. The proposed scheme is accessed on a virtualized environment that simulates a P2P-friendly cloud system. The system shows high accuracy in differentiating P2P file-sharing hosts from ordinary hosts. Its tunability regarding monitoring cost, system response time, and prediction accuracy is demonstrated by a series of experiments. Further study on feature selection is pursued to identify the most essential discriminators that contribute most to the classification. Experimental results show that an equally accurate system could be obtained using only 3 out of the 18 defined discriminators, which further reduces the monitoring cost and enhances the adaptability of the system.},
keywords={},
doi={10.1587/transinf.E95.D.2888},
ISSN={1745-1361},
month={December},}

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TY - JOUR
TI - Towards Cost-Effective P2P Traffic Classification in Cloud Environment
T2 - IEICE TRANSACTIONS on Information
SP - 2888
EP - 2897
AU - Tao BAN
AU - Shanqing GUO
AU - Masashi ETO
AU - Daisuke INOUE
AU - Koji NAKAO
PY - 2012
DO - 10.1587/transinf.E95.D.2888
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2012
AB - Characterization of peer-to-peer (P2P) traffic is an essential step to develop workload models towards capacity planning and cyber-threat countermeasure over P2P networks. In this paper, we present a classification scheme for characterizing P2P file-sharing hosts based on transport layer statistical features. The proposed scheme is accessed on a virtualized environment that simulates a P2P-friendly cloud system. The system shows high accuracy in differentiating P2P file-sharing hosts from ordinary hosts. Its tunability regarding monitoring cost, system response time, and prediction accuracy is demonstrated by a series of experiments. Further study on feature selection is pursued to identify the most essential discriminators that contribute most to the classification. Experimental results show that an equally accurate system could be obtained using only 3 out of the 18 defined discriminators, which further reduces the monitoring cost and enhances the adaptability of the system.
ER -