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Amplified locality-sensitive hashing for privacy-preserving distributed service recommendation

conference contribution
posted on 2017-01-01, 00:00 authored by L Qi, W Dou, X Zhang, Shui Yu
With the ever-increasing volume of services registered in various web communities, service recommendation techniques, e.g., Collaborative Filtering (i.e., CF) have provided a promising way to alleviate the heavy burden on the service selection decisions of target users. However, traditional CF-based service recommendation approaches often assume that the recommendation bases, i.e., historical service quality data are centralized, without considering the distributed service recommendation scenarios as well as the resulted privacy leakage risks. In view of this shortcoming, Locality-Sensitive Hashing (LSH) technique is recruited in this paper to protect the private information of users when distributed service recommendations are made. Furthermore, LSH is essentially a probability-based search technique and hence may generate “False-positive” or “False-negative” recommended results; therefore, we amplify LSH by AND/OR operations to improve the recommendation accuracy. Finally, through a set of experiments deployed on a real distributed service quality dataset, i.e., WS-DREAM, we validate the feasibility of our proposed recommendation approach named DistSR Amplify-LSH in terms of recommendation accuracy and efficiency while guaranteeing privacy-preservation in the distributed environment.

History

Event

Security, Privacy, and Anonymity in Computation, Communication, and Storage. International Conference (10th : 2017 : Guangzhou, China)

Volume

10656 LNCS

Pagination

280 - 297

Publisher

Springer International

Location

Guangzhou, China

Place of publication

Cham, Switzerland

Start date

2017-12-12

End date

2017-12-15

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783319723884

Language

eng

Publication classification

E Conference publication; E1 Full written paper - refereed

Copyright notice

2017, Springer International Publishing AG

Editor/Contributor(s)

D Hutchison, T Kanade, J Kittler, J Kleinberg, F Mattern, J Mitchell, M Naor, C Rangan, B Steffen, D Terzopoulos, D Tygar, G Weikum

Title of proceedings

SpaCCS 2017 : Proceedings of the 10th Security, Privacy, and Anonymity in Computation, Communication, and Storage International Conference