Unpublished conference/Abstract (Scientific congresses, symposiums and conference proceedings)
Protect both Integrity and Confidentiality in Outsourcing Collaborative Filtering Computations
Pejo, Balazs; Tang, Qiang; Wang, Husen
20169th IEEE International Conference on Cloud Computing (IEEE CLOUD)
 

Files


Full Text
paper 10361.pdf
Publisher postprint (241.18 kB)
Short Paper
Download
Full Text Parts
ppt.pdf
Publisher postprint (528.52 kB)
Presentation
Download

All documents in ORBilu are protected by a user license.

Send to



Details



Keywords :
Collaborative Filtering; Integrity; Verification
Abstract :
[en] In the cloud computing era, in order to avoid the computational burdens, many recommendation service providers tend to outsource their collaborative filtering computations to third-party cloud servers. In order to protect service quality, the integrity of computation results needs to be guaranteed. In this paper, we analyze two integrity verification approaches by Vaidya et al. and demonstrate their performances. In particular, we analyze the verification via auxiliary data approach which is only briefly mentioned in the original paper, and demonstrate the experimental results. We then propose a new solution to outsource all computations of the weighted Slope One algorithm in two-server setting and provide experimental results.
Disciplines :
Computer science
Author, co-author :
Pejo, Balazs ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Tang, Qiang;  Luxembourg Institute of Science & Technology - LIST
Wang, Husen;  Luxembourg Institute of Science & Technology - LIST
External co-authors :
no
Language :
English
Title :
Protect both Integrity and Confidentiality in Outsourcing Collaborative Filtering Computations
Publication date :
27 June 2016
Event name :
9th IEEE International Conference on Cloud Computing (IEEE CLOUD)
Event place :
San Francisco, United States
Event date :
June 27 - July 2, 2016
Audience :
International
Focus Area :
Security, Reliability and Trust
Available on ORBilu :
since 16 January 2017

Statistics


Number of views
106 (16 by Unilu)
Number of downloads
189 (9 by Unilu)

Bibliography


Similar publications



Contact ORBilu