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Please use this identifier to cite or link to this item:
http://hdl.handle.net/1783.1/2294
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| Title: | A mutual anonymous peer-to-peer protocol design |
| Authors: | Han, Jinsong Liu, Yunhao Xiao, Li Xiao, Renyi Ni, Lionel M. |
| Keywords: | Peer-to-peer Protocol design Mutual anonymous Protocol P2P |
| Issue Date: | Apr-2005 |
| Citation: | 19th IEEE International Parallel and Distributed Processing Symposium, April 4-8, 2005 |
| Abstract: | Peer-to-Peer (P2P) computing has become a popular application model because of its easy resource sharing pattern and powerful query search scheme. However, decentralized P2P architecture is scarcely seen to deploy the anonymity on its peers. In this paper, we propose a mutual anonymity protocol, called Secret-sharing-based Mutual Anonymity Protocol (SSMP), for decentralized P2P systems. SSMP employs Shamirs’ secret sharing scheme to allow peers to issue queries and responders to deliver requested files anonymously. Compared with previous designs, SSMP achieves mutual anonymity in P2P systems with a high degree of anonymity and a low cryptography processing overhead. We evaluate SSMP by comprehensive simulations. |
| Rights: | © 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. |
| URI: | http://hdl.handle.net/1783.1/2294 |
| Appears in Collections: | CSE Conference Papers
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| IPDPS05SSMPCamrea.pdf | pre-published version | 537Kb | Adobe PDF | View/Open |
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