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1
Trust-based Privacy Preservation for Peer-to-peer Data Sharing
Y. Lu= , W. Wang, D. Xu, and B. Bhargava
yilu, wangwc, dxu, bb @ cs.purdue.edu
Depar= tment of Computer Sciences
Purdue University=
The work is supported by NSF ANI-0219110 and IIS-0209059
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2 =
Problem statement
nPrivacy in peer-to-peer systems is <= span style=3D'position:absolute;top:28.74%;left:13.85%;width:89.13%;height:7.5= %'>different from the anonymity problem
= nPrese= rve privacy of requester
nA me= chanism is needed to remove the association between the identity of= the requester and the data needed
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Proposed solution
nA mechanism is proposed that allows the peers to acquire data th= rough trusted proxies to preserve privacy of requester
nThe data request is handled through the peer’s proxies
nThe proxy can become a supplier later and mask the original requester
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Related work
nTrust in privacy preservation
nAuthorization based on evidence and trust, [Bhargava and Zhong, DaWaK’02]
nDeveloping pervasive trust [Lilien, CGW’03] =
nHiding the subject in a crowd
nK-anonymity [Sweeney, UFKS’02]
nBroadcast and multicast [Scarlata et al, INCP’01]
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Related work (2)
nFixed servers and proxies
nPublius [Waldman et al, USENIX’00]
nBuilding a multi-hop path to hide the real source and destination&#= 13;
nFreeNet [Clarke et al, IC’02] =
nCrowds [Reiter and Rubin, ACM TISS’98]
nOnion routing [Goldschlag et al, ACM Commu.’99]
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Related work (3)
n     [Sherwood e= t al, IEEE SSP’02]
n    provides sender-rece= iver anonymity by transmitting packets to a broadcast group <= /span>
nHerbivore [Goel et al, Cornell Univ Tech Report’03]
nProvides provable anonymity in peer-to-peer communication systems by adopting dining cryptographer networks
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Privacy measurement
nA tuple <requester ID, data handle, data content> is defined to describe a data = acquirement.
nFor each element, “0” means that the = peer knows nothing, while “1” means that i= t knows everything. =
nA state in which the requester’s privacy is= compromised can be represented as a vector <1, 1, y>, (y Є [0,1= ]) from which one can link the I= D of the requester to the data that it is interested in.
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For example, line k represents= the states that the requester’s privacy is compromised.
Privacy measurement (2)
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