G. de Veciana, PI, U.T. Austin, and G. Kesidis, PI, Penn State

Award Abstract:

Peer-to-peer systems have seen continued growth, in terms of traffic volume, and as the architecture of choice to build new applications and network services ? notable benefits lie in their distributed design leading to higher reliability and flexibility. However as users/peers increasingly become content providers, and generally conduct more of their business on the network, privacy is a critical concern.

By leveraging peers? trust relationships through referral mechanisms based on underlying reputation systems, applications that deliver a new standard of privacy are being devised. Peer-to-peer systems that dynamically adapt, in a distributed and scalable manner, based on the outcomes of peer transactions, are being modeled and analyzed. The focus is on unstructured networks where peer-membership correlations among communities of interest can be learned to improve the search performance of reputation-biased random walks and limited-scope flooding. Content-sharing applications are being designed based that leverage this framework to incentivize cooperative behavior while enabling collaborative filtering and content pushing.

Expected results include the development analysis and testing of a new framework for privacy-preserving search for large-scale, unstructured, on-line, peer-to-peer networks. Complementary incentive mechanisms resulting in improve file sharing and promoting honest referrals will be devised. The results will be disseminated through peer-reviewed venues and, where possible, industry concerns, while data and simulation tools are made available on the web.

The efforts impact will lie in contributing new ways to improve privacy and promote more honest and efficient cooperation in large-scale on-line peer-to-peer systems, for content sharing, as well as a broader set of social networking applications.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Type
Standard Grant (Standard)
Application #
0916179
Program Officer
Thyagarajan Nandagopal
Project Start
Project End
Budget Start
2009-09-01
Budget End
2013-08-31
Support Year
Fiscal Year
2009
Total Cost
$150,000
Indirect Cost
Name
Pennsylvania State University
Department
Type
DUNS #
City
University Park
State
PA
Country
United States
Zip Code
16802