Preserving privacy in collaborative filtering through distributed aggregation of offline profiles

RecSys'09 - Proceedings of the 3rd ACM Conference on Recommender Systems

Volumn , Issue , 2009, Pages 157-164

  Shokri, Reza ^a   Pedarsani, Pedram ^a   Theodorakopoulos, George ^a   Hubaux, Jean Pierre ^a  

^a EPFL   (Switzerland)

Author keywords

Privacy accuracy tradeoff; Recommender systems

Indexed keywords

CENTRAL SERVERS; COLLABORATIVE FILTERING; DATA SETS; DIRECT CONTACT; GRAPH MATCHINGS; OFFLINE; PRIVACY AND ACCURACY; RECOMMENDATION ACCURACY; RECOMMENDER SYSTEMS; SYSTEM LEVELS; UNTRUSTED SERVER;

PATTERN MATCHING;

COMMUNICATION CHANNELS (INFORMATION THEORY);

EID: 72249112536     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1639714.1639741     Document Type: Conference Paper

References (16)

1. Netflix prize, http://www.netflixprize.com.
2. Rummble, http://www.rummble.com.
3. W. Ahmad and A. Khokhar. An architecture for privacy preserving collaborative filtering on web portals. In International Symposium on Information Assurance and Security (IAS), Aug. 2007.
4. S. Berkovsky, Y. Eytani, T. Kuflik, and F. Ricci. Enhancing privacy and preserving accuracy of a distributed collaborative filtering. In Proceedings of ACM RecSys, 2007.
5. J. S. Breese, D. Heckerman, and C. Kadie. Empirical analysis of predictive algorithms for collaborative filtering. 1998.
6. J. Canny. Collaborative filtering with privacy. In IEEE Symposium on Security and Privacy, 2002.
7. J. Canny. Collaborative filtering with privacy via factor analysis. In ACM SIGIR, 2002.
8. J. L. Herlocker, J. A. Konstan, A. Borchers, and J. Riedl. An algorithmic framework for performing collaborative filtering. In ACM SIGIR, 1999.
9. N. Lathia, S. Hailes, and L. Capra. Private distributed collaborative filtering using estimated concordance measures. In Proceedings of ACM RecSys, 2007.
10. B. Luo and E. R. Hancock. Structural graph matching using the em algorithm and singular value decomposition. IEEE Trans. Pattern Anal. Mach. Intell., 23(10), 2001.
11. B. N. Miller, J. A. Konstan, and J. Riedl. Pocketlens: Toward a personal recommender system. ACM Trans. Inf. Syst., 22(3), 2004.
12. R. Myers, R. C. Wilson, and E. R. Hancock. Bayesian graph edit distance. IEEE Trans. Pattern Anal. Mach. Intell., 22(6), 2000.
13. A. Narayanan and V. Shmatikov. Robust de-anonymization of large sparse datasets. In IEEE Symposium on Security and Privacy, 2008.
14. H. Polat and W. Du. Privacy-preserving collaborative filtering using randomized perturbation techniques. In Proceedings of IEEE ICDM, 2003.
15. P. Resnick, N. Iacovou, M. Suchak, P. Bergstorm, and J. Riedl. Grouplens: An open architecture for collaborative filtering of netnews. In Proceedings of ACM Conference on Computer Supported Cooperative Work, 1994.
16. B. Sarwar, G. Karypis, J. Konstan, and J. Reidl. Item-based collaborative filtering recommendation algorithms. In WWW, 2001.