IEICE TRANSACTIONS on Information
Reputation-Based Colluder Detection Schemes for Peer-to-Peer Content Delivery Networks
Summary :
Recently Peer-to-Peer Content Delivery Networks (P2P CDNs) have attracted considerable attention as a cost-effective way to disseminate digital contents to paid users in a scalable and dependable manner. However, due to its peer-to-peer nature, it faces threat from “colluders” who paid for the contents but illegally share them with unauthorized peers. This means that the detection of colluders is a crucial task for P2P CDNs to preserve the right of contents holders and paid users. In this paper, we propose two colluder detection schemes for P2P CDNs. The first scheme is based on the reputation collected from all peers participating in the network and the second scheme improves the quality of colluder identification by using a technique which is well known in the field of system level diagnosis. The performance of the schemes is evaluated by simulation. The simulation results indicate that even when 10% of authorized peers are colluders, our schemes identify all colluders without causing misidentifications.
- Publication
- IEICE TRANSACTIONS on Information Vol.E96-D No.12 pp.2696-2703
- Publication Date
- 2013/12/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E96.D.2696
- Type of Manuscript
- Special Section PAPER (Special Section on Parallel and Distributed Computing and Networking)
- Category
Authors
Ervianto ABDULLAH
Hiroshima University
Satoshi FUJITA
Hiroshima University
Keyword
Latest Issue
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Ervianto ABDULLAH, Satoshi FUJITA, "Reputation-Based Colluder Detection Schemes for Peer-to-Peer Content Delivery Networks" in IEICE TRANSACTIONS on Information,
vol. E96-D, no. 12, pp. 2696-2703, December 2013, doi: 10.1587/transinf.E96.D.2696.
Abstract: Recently Peer-to-Peer Content Delivery Networks (P2P CDNs) have attracted considerable attention as a cost-effective way to disseminate digital contents to paid users in a scalable and dependable manner. However, due to its peer-to-peer nature, it faces threat from “colluders” who paid for the contents but illegally share them with unauthorized peers. This means that the detection of colluders is a crucial task for P2P CDNs to preserve the right of contents holders and paid users. In this paper, we propose two colluder detection schemes for P2P CDNs. The first scheme is based on the reputation collected from all peers participating in the network and the second scheme improves the quality of colluder identification by using a technique which is well known in the field of system level diagnosis. The performance of the schemes is evaluated by simulation. The simulation results indicate that even when 10% of authorized peers are colluders, our schemes identify all colluders without causing misidentifications.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E96.D.2696/_p
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@ARTICLE{e96-d_12_2696,
author={Ervianto ABDULLAH, Satoshi FUJITA, },
journal={IEICE TRANSACTIONS on Information},
title={Reputation-Based Colluder Detection Schemes for Peer-to-Peer Content Delivery Networks},
year={2013},
volume={E96-D},
number={12},
pages={2696-2703},
abstract={Recently Peer-to-Peer Content Delivery Networks (P2P CDNs) have attracted considerable attention as a cost-effective way to disseminate digital contents to paid users in a scalable and dependable manner. However, due to its peer-to-peer nature, it faces threat from “colluders” who paid for the contents but illegally share them with unauthorized peers. This means that the detection of colluders is a crucial task for P2P CDNs to preserve the right of contents holders and paid users. In this paper, we propose two colluder detection schemes for P2P CDNs. The first scheme is based on the reputation collected from all peers participating in the network and the second scheme improves the quality of colluder identification by using a technique which is well known in the field of system level diagnosis. The performance of the schemes is evaluated by simulation. The simulation results indicate that even when 10% of authorized peers are colluders, our schemes identify all colluders without causing misidentifications.},
keywords={},
doi={10.1587/transinf.E96.D.2696},
ISSN={1745-1361},
month={December},}
Copy
TY - JOUR
TI - Reputation-Based Colluder Detection Schemes for Peer-to-Peer Content Delivery Networks
T2 - IEICE TRANSACTIONS on Information
SP - 2696
EP - 2703
AU - Ervianto ABDULLAH
AU - Satoshi FUJITA
PY - 2013
DO - 10.1587/transinf.E96.D.2696
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E96-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2013
AB - Recently Peer-to-Peer Content Delivery Networks (P2P CDNs) have attracted considerable attention as a cost-effective way to disseminate digital contents to paid users in a scalable and dependable manner. However, due to its peer-to-peer nature, it faces threat from “colluders” who paid for the contents but illegally share them with unauthorized peers. This means that the detection of colluders is a crucial task for P2P CDNs to preserve the right of contents holders and paid users. In this paper, we propose two colluder detection schemes for P2P CDNs. The first scheme is based on the reputation collected from all peers participating in the network and the second scheme improves the quality of colluder identification by using a technique which is well known in the field of system level diagnosis. The performance of the schemes is evaluated by simulation. The simulation results indicate that even when 10% of authorized peers are colluders, our schemes identify all colluders without causing misidentifications.
ER -
English
