Privacy preservation in peer to peer gossiping networks in presence of a

Al-Aggan, Mohammad

Description

Niveau: Supérieur, Master
Privacy preservation in peer-to-peer gossiping networks in presence of a passive adversary ? Mohammad ALAGGAN ? Supervisors: Anne-Marie Kermarrec, Sebastien Gambs INRIA - ASAP Research Team Masters by Research in Computer Science (IFSIC) June 24, 2010 A thesis submitted in partial fulfillment of the requirements for the degree of Masters by research in Computer Science from IRISA / Universite Rennes 1 Abstract In the Web 2.0, more and more personal data are released by users (queries, social networks, geo-located data,. . . ), which create a huge pool of useful information to leverage in the context of search or recommen- dation for instance. In fully decentralized systems, tapping on the power of this information usually involves a clustering process that relies on an exchange of personal data (such as user profiles) to compute the similarity between users. In this internship, we address the problem of computing similarity between users while preserving their privacy and without relying on a central entity, with regards to a passive adversary. ?This research is supported by the Gossple ERC Starting Grant number 204742. ?Funded by a grant from Fondation Michel Metivier. 1 du m as -0 05 30 60 3, v er sio n 1 - 2 9 O ct 2 01 0

• private similarity


• party computation


• distributed systems


• model focuses


• system model


• differentially private


• item domain


• threshold similarity


• noise


• privacy

Sujets

• Métivier
• Kermarrec
• Distributed computing
• System model
• Privacy

Informations

• Publié par: dumas_ccsd
• Nombre de lectures: 16
• Langue: English
• Poids de l'ouvrage: 1 Mo

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