A Private and Reliable Recommendation System for Social Networks
T. Hoens, M. Blanton, and N. Chawla. Proceedings of the 2010 IEEE Second International Conference on Social Computing, page 816--825. Washington, DC, USA, IEEE Computer Society, (2010)
DOI: 10.1109/SocialCom.2010.124
Abstract
With the proliferation of internet-based social networks into our lives, new mechanisms to control the release and use of personal data are required. As a step toward this goal, we develop a recommendation system which protects the privacy of user answers while allowing them to learn an aggregate weighted average of ratings. Due to the use of social network connections, the querier obtains a more relevant and trustworthy result than what generic anonymous recommendation systems can provide, while at the same time preserving user privacy. We also give experimental performance results for our solution and several recently developed secure computation techniques, which is of independent interest.
Description
A Private and Reliable Recommendation System for Social Networks
%0 Conference Paper
%1 hoens2010private
%A Hoens, T. Ryan
%A Blanton, Marina
%A Chawla, Nitesh V.
%B Proceedings of the 2010 IEEE Second International Conference on Social Computing
%C Washington, DC, USA
%D 2010
%I IEEE Computer Society
%K privacy recommender social-networks
%P 816--825
%R 10.1109/SocialCom.2010.124
%T A Private and Reliable Recommendation System for Social Networks
%U http://dx.doi.org/10.1109/SocialCom.2010.124
%X With the proliferation of internet-based social networks into our lives, new mechanisms to control the release and use of personal data are required. As a step toward this goal, we develop a recommendation system which protects the privacy of user answers while allowing them to learn an aggregate weighted average of ratings. Due to the use of social network connections, the querier obtains a more relevant and trustworthy result than what generic anonymous recommendation systems can provide, while at the same time preserving user privacy. We also give experimental performance results for our solution and several recently developed secure computation techniques, which is of independent interest.
%@ 978-0-7695-4211-9
@inproceedings{hoens2010private,
abstract = {With the proliferation of internet-based social networks into our lives, new mechanisms to control the release and use of personal data are required. As a step toward this goal, we develop a recommendation system which protects the privacy of user answers while allowing them to learn an aggregate weighted average of ratings. Due to the use of social network connections, the querier obtains a more relevant and trustworthy result than what generic anonymous recommendation systems can provide, while at the same time preserving user privacy. We also give experimental performance results for our solution and several recently developed secure computation techniques, which is of independent interest.},
acmid = {1907393},
added-at = {2011-12-20T00:08:42.000+0100},
address = {Washington, DC, USA},
author = {Hoens, T. Ryan and Blanton, Marina and Chawla, Nitesh V.},
biburl = {https://www.bibsonomy.org/bibtex/2f5e17b54854d827159b3703bb489cc0d/beate},
booktitle = {Proceedings of the 2010 IEEE Second International Conference on Social Computing},
description = {A Private and Reliable Recommendation System for Social Networks},
doi = {10.1109/SocialCom.2010.124},
interhash = {e7fa76dccf363d7266c6ffd6433b6ec1},
intrahash = {f5e17b54854d827159b3703bb489cc0d},
isbn = {978-0-7695-4211-9},
keywords = {privacy recommender social-networks},
numpages = {10},
pages = {816--825},
publisher = {IEEE Computer Society},
series = {SOCIALCOM '10},
timestamp = {2011-12-20T00:08:42.000+0100},
title = {A Private and Reliable Recommendation System for Social Networks},
url = {http://dx.doi.org/10.1109/SocialCom.2010.124},
year = 2010
}