Privacy preserving group ranking

Lingjun Li, Xinxin Zhao, Guoliang Xue, Gabriel Silva

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


Group ranking is a necessary process used to find the best participant from a group. Group ranking has many applications, including online marketing, personal interests matching and proposal ranking. In an online virtual environment, participants want to do group ranking without leaking any of their private information. In this work, we generalize this scenario as a privacy preserving group ranking problem and formulate the privacy requirements of this problem. We propose a fully distributed privacy preserving group ranking framework and prove its security in the honest but curious model. The core of our framework is a novel multiparty sorting protocol, which guarantees that an adversary cannot link the private information to its owner's identity as long as the owner's final ranking is hidden from the adversary. Our protocol is efficient in computational overhead and communication rounds compared to existing works, as demonstrated by our analysis and simulation.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Distributed Computing Systems
Number of pages10
StatePublished - 2012
Event32nd IEEE International Conference on Distributed Computing Systems, ICDCS 2012 - Macau, China
Duration: Jun 18 2012Jun 21 2012


Other32nd IEEE International Conference on Distributed Computing Systems, ICDCS 2012

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Software


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