TAILIEUCHUNG - Trust-based Privacy Preservation for Peer-to-peer Data Sharing

Trust-based Privacy Preservation for Peer-to-peer Data Sharing provides about Problem statement, Proposed solution, Related work, Privacy measurement, Mitigating collusion, Trust based privacy preservation scheme, Trustworthiness of peers. | Trust-based Privacy Preservation for Peer-to-peer Data Sharing Y. Lu, W. Wang, D. Xu, and B. Bhargava yilu, wangwc, dxu, bb @ Department of Computer Sciences Purdue University The work is supported by NSF ANI-0219110 and IIS-0209059 Problem statement Privacy in peer-to-peer systems is different from the anonymity problem Preserve privacy of requester A mechanism is needed to remove the association between the identity of the requester and the data needed Proposed solution A mechanism is proposed that allows the peers to acquire data through trusted proxies to preserve privacy of requester The data request is handled through the peer’s proxies The proxy can become a supplier later and mask the original requester Related work Trust in privacy preservation Authorization based on evidence and trust, [Bhargava and Zhong, DaWaK’02] Developing pervasive trust [Lilien, CGW’03] Hiding the subject in a crowd K-anonymity [Sweeney, UFKS’02] Broadcast and multicast [Scarlata et al, INCP’01] Related work (2) Fixed servers and proxies Publius [Waldman et al, USENIX’00] Building a multi-hop path to hide the real source and destination FreeNet [Clarke et al, IC’02] Crowds [Reiter and Rubin, ACM TISS’98] Onion routing [Goldschlag et al, ACM Commu.’99] Related work (3) [Sherwood et al, IEEE SSP’02] provides sender-receiver anonymity by transmitting packets to a broadcast group Herbivore [Goel et al, Cornell Univ Tech Report’03] Provides provable anonymity in peer-to-peer communication systems by adopting dining cryptographer networks Privacy measurement A tuple is defined to describe a data acquirement. For each element, “0” means that the peer knows nothing, while “1” means that it knows everything. A state in which the requester’s privacy is compromised can be represented as a vector , (y Є [0,1]) from which one can link the ID of the requester to the data that it is interested in. For example,

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