TY - GEN
T1 - LIP3
T2 - 15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015
AU - Wang, Yufeng
AU - Chen, Xiaohong
AU - Jin, Qun
AU - Ma, Jianhua
N1 - Funding Information:
This work was supported by the NSFC 61171092, the JiangSu Educational Bureau Project under Grant 14KJA510004, and Prospective Research Project on Future Networks (JiangSu Future Networks Innovation Institute).
PY - 2015
Y1 - 2015
N2 - Recently, Device to Device (D2D) based mobile social networking in proximity (MSNP) has witnessed great development on smartphones, which enable actively/passively and continuously seek for relevant value in one’s physical proximity, through direct communicating with other individuals within the communication range, without the support of centralized networking infrastructure. Specially, a user would like to find out and interact with some strangers with similar interest in vicinity through profile matching. However, in matching process, individuals always have to reveal their personal and private profiles to strangers, which conflicts with users’ growing privacy concerns. To achieve privacy preserving profile matching (i.e., friend discovery), many schemes are proposed based on homomorphic and commutative encryption, which bring tremendous computation and communication overheads, and are not practical for the resource limited mobile devices in MSNP. In this paper we adapt Confusion Matrix Transformation (CMT) method to design a Lightweighted fIne-grained Privacy-Preserving Profile matching mechanism, LIP3, which can not only efficiently realize privacy-preserving profile matching, but obtain the strict measurement of cosine similarity between individuals, while other existing CMT-based schemes can only roughly estimate the matching value.
AB - Recently, Device to Device (D2D) based mobile social networking in proximity (MSNP) has witnessed great development on smartphones, which enable actively/passively and continuously seek for relevant value in one’s physical proximity, through direct communicating with other individuals within the communication range, without the support of centralized networking infrastructure. Specially, a user would like to find out and interact with some strangers with similar interest in vicinity through profile matching. However, in matching process, individuals always have to reveal their personal and private profiles to strangers, which conflicts with users’ growing privacy concerns. To achieve privacy preserving profile matching (i.e., friend discovery), many schemes are proposed based on homomorphic and commutative encryption, which bring tremendous computation and communication overheads, and are not practical for the resource limited mobile devices in MSNP. In this paper we adapt Confusion Matrix Transformation (CMT) method to design a Lightweighted fIne-grained Privacy-Preserving Profile matching mechanism, LIP3, which can not only efficiently realize privacy-preserving profile matching, but obtain the strict measurement of cosine similarity between individuals, while other existing CMT-based schemes can only roughly estimate the matching value.
KW - Confusion matrix transformation
KW - Mobile social networking in proximity (MSNP)
KW - Privacy-Preserving
KW - Profile matching
UR - http://www.scopus.com/inward/record.url?scp=84952045308&partnerID=8YFLogxK
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U2 - 10.1007/978-3-319-27161-3_15
DO - 10.1007/978-3-319-27161-3_15
M3 - Conference contribution
AN - SCOPUS:84952045308
SN - 9783319271606
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 166
EP - 176
BT - Algorithms and Architectures for Parallel Processing - ICA3PP International Workshops and Symposiums, Proceedings
A2 - Perez, Gregorio Martinez
A2 - Zomaya, Albert
A2 - Li, Kenli
A2 - Wang, Guojun
PB - Springer Verlag
Y2 - 18 November 2015 through 20 November 2015
ER -