TY - GEN
T1 - Semantics-enhanced privacy recommendation for social networking sites
AU - Li, Qingrui
AU - Li, Juan
AU - Wang, Hui
AU - Ginjala, Ashok
PY - 2011
Y1 - 2011
N2 - Privacy protection is a vital issue for safe social interactions within social networking sites (SNS). Although SNSs such as My Space and Face book allow users to configure their privacy settings, it is not a simple task for normal users with hundreds of online friends. In this paper, we propose an intelligent semantics-based privacy configuration system, named SPAC, to automatically recommend privacy settings for SNS users. SPAC learns users' privacy configuration patterns and make predictions by utilizing machine learning techniques on users' profiles and privacy setting history. To increase the accuracy of the predicted privacy settings, especially in the context of heterogeneous user profiles, we enhance privacy configuration predictor by integrating it with structured semantic knowledge in the SNS. This, in turn, allows SPAC to make inferences based on additional source of knowledge, resulting in improved accuracy of privacy recommendation. Our experimental results have proven the effectiveness of our approach.
AB - Privacy protection is a vital issue for safe social interactions within social networking sites (SNS). Although SNSs such as My Space and Face book allow users to configure their privacy settings, it is not a simple task for normal users with hundreds of online friends. In this paper, we propose an intelligent semantics-based privacy configuration system, named SPAC, to automatically recommend privacy settings for SNS users. SPAC learns users' privacy configuration patterns and make predictions by utilizing machine learning techniques on users' profiles and privacy setting history. To increase the accuracy of the predicted privacy settings, especially in the context of heterogeneous user profiles, we enhance privacy configuration predictor by integrating it with structured semantic knowledge in the SNS. This, in turn, allows SPAC to make inferences based on additional source of knowledge, resulting in improved accuracy of privacy recommendation. Our experimental results have proven the effectiveness of our approach.
KW - ontology
KW - privacy
KW - recommendation
KW - semantics
KW - social network
UR - http://www.scopus.com/inward/record.url?scp=84862941392&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84862941392&partnerID=8YFLogxK
U2 - 10.1109/TrustCom.2011.31
DO - 10.1109/TrustCom.2011.31
M3 - Conference contribution
AN - SCOPUS:84862941392
SN - 9780769546001
T3 - Proc. 10th IEEE Int. Conf. on Trust, Security and Privacy in Computing and Communications, TrustCom 2011, 8th IEEE Int. Conf. on Embedded Software and Systems, ICESS 2011, 6th Int. Conf. on FCST 2011
SP - 226
EP - 233
BT - Proc. 10th IEEE Int. Conf. on Trust, Security and Privacy in Computing and Communications, TrustCom 2011, 8th IEEE Int. Conf. on Embedded Software and Systems, ICESS 2011, 6th Int. Conf. FCST 2011
T2 - 10th IEEE Int. Conf. on Trust, Security and Privacy in Computing and Communications, TrustCom 2011, 8th IEEE Int. Conf. on Embedded Software and Systems, ICESS 2011, 6th Int. Conf. on Frontier of Computer Science and Technology, FCST 2011
Y2 - 16 November 2011 through 18 November 2011
ER -