Privacy-Preserving Distributed Collaborative Filtering Using Secure Set Operations


(*) Corresponding author


Authors' affiliations


DOI's assignment:
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)

Abstract


At present, collaborative filtering has been wildly used in many fields such as e-commerce, search engineering, and etc. To produce a better recommendation, many data owners want to collaborative with each other to build a shared model. Considering the privacy problem, the data owner is reluctant to reveal its data to others. To solve this problem, we present a privacy-preserving approach using the secure set operations and encryption methods. In our method, firstly the private set intersection cardinality protocol is adopted to compute the user similarities. Then our method uses the homomorphic encryption to compute the predicted rating values for the unrated items. Finally, the model recommends the top-k unrated items to each user. We show that the distributed collaborative filtering based on our approach can provide zero loss of accuracy in the recommendation while preserving the privacy of different data owners.
Copyright © 2013 Praise Worthy Prize - All rights reserved.

Keywords


Privacy Preserving; Set Operations; Collaborative Filtering

Full Text:

PDF


References


Sneha, Y.S., Mahadevan, G., Parvathi, R.M.S., Recommender system based on user ratings: A comprehensive study and future challenges, (2013) International Review on Computers and Software (IRECOS), 8 (7), pp. 1624-1635.

Wu, J., Wu, Z., Mobile location-aware personalized recommendation with clustering-based collaborative filtering, (2012) International Review on Computers and Software (IRECOS), 7 (5), pp. 2231-2238.

Yao, L., Yang, W., A context-aware recommender for trustworthy service, (2012) International Review on Computers and Software (IRECOS), 7 (6), pp. 3354-3359.

Tripathy, P.K., Biswal, D., Multiple server indirect security authentication protocol for mobile networks using elliptic curve cryptography (ECC), (2013) International Review on Computers and Software (IRECOS), 8 (7), pp. 1571-1577.

M. Eslamnezhad Namin, F. Badihiyeh Aghdam, M. Hosseinzadeh, A Secure and Efficient RFID Mutual Authentication Protocol, (2011) International Journal on Communications Antenna and Propagation (IRECAP), 1 (5), pp. 429-433.

H. Ploat, W. Du, Privacy-preserving Top N Recommendation on Distributed Data, Journal of American society for Information Science and Technology, Vol.59, pp.1093-1108, 2008.

I. Yakut, H. Polat, Arbitrarily Distributed Data-based Recommendations with Privacy, Data and Knowledge Engineering, Vol. 72, pp.239-256, 2012.

H. Ploat, W. Du, Privacy-preserving Collaborative Filtering on Vertically Partitioned Data, Proceedings of the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (Page: 651-658 Year of Publication: 2005 ISBN: 3-540-29244-6).

C. Kaleli, H. Polat, Providing Naive Bayesian Classifier-based Private Recommendations on Partitioned Data, Proceedings of the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (Page: 515-522 Year of Publication: 2007 ISBN: 978-3-540-74975-2).

I. Yakut, H. Polat, Privacy-preserving SVD-based Collaborative Filtering on Partitioned Data, International Journal of Information Technology and Decision Making, Vol. 9, pp.473-502, 2010.

L. Egghe, New Relations between Similarity Measures for Vectors Based on Vector Norms. Journal of the American Society for Information Science and Technology, Vol. 60, n. 2, pp. 232-239, 2009.

Novel Secure Code Encryption Techniques Using Crypto Based Indexed Table for Highly Secured Software

E.D. Cristofaro, P. Gasti, G. Tsudik, Fast and Private Computation of Cardinality of Set Intersection and Union, Proceedings of the 11th Int. Conf. on Cryptology and Network Security (Page: 218-231 Year of Publication: 2012 ISBN: 978-3-642-35403-8).

P. Paillier, Public Key Cryptosystem Based on Composite Degree Residuosity Classes, Proceedings of the 17th Int. Conf. on Theory and application of cryptographic techniques (Page: 223-238 Year of Publication: 1999 ISBN: 3-540-65889-0).

O. Goldreich, Foundations of Cryptography: Volume II, Basic Applications. (Cambridge: Cambridge University Press, 2004).

P. Massa, P. Avesani, Trust Aware Bootstrapping Recommender Systems, Proceedings of the 17th European Conference on Artificial Intelligence Workshop on Recommender Systems (Page: 29-33 Year of Publication: 2006 ISBN: 1-58603-642-4).

F. Celli, F. L. Lascio, M. Magnani, and etc, Social Network Data and Practices: the Case of Friendfeed. Proceedings of the 3rd International Conference Social Computing, Behavioral Modeling and Prediction (Page: 346–353 Year of Publication: 2010 ISBN: 978-3-642-12078-7).

D.C. Nie, M.J. Ding, and etc, Social interest for user selecting items in recommender systems, International Journal of Modern Physics C, Vol. 24, n. 4, 1350022, 2013.


Refbacks

  • There are currently no refbacks.


Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize