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A Privacy Preserving Aggregation Scheme for Fog-Based Recommender System
conference contribution
posted on 2020-01-01, 00:00 authored by Wang (Tony) Xiaodong, B Gu, Youyang Qu, Y Ren, Yong XiangYong Xiang, Longxiang GaoLongxiang GaoWith the rapid growth in the number of smart devices and explosive data generated every day by the mobile users, cloud computing comes to the bottleneck due to the far-off transmission and bandwidth limitation. Fog computing has been introduced as one of the promising solutions to meet the requirements under Internet of Things (IoT) scenarios such as location awareness and real-time services. The study of fog-based applications has become an attractive and important potential trend. The existing research about fog-based recommender systems focus on providing personalized and localized services to users while serving as a fog computing optimization tool in the system. However, there is little research about how to preserve user privacy in fog-based recommender systems. In this paper, we propose a novel privacy preserving aggregation scheme to handle the privacy issue for fog-based recommender systems.
History
Event
Network and System Security. Conference (2020 : Melbourne Vic.)Volume
12570Series
Lecture Notes in Computer SciencePagination
408 - 418Publisher
SpringerLocation
Melbourne, AustraliaPlace of publication
Berlin, GermanyPublisher DOI
Start date
2020-11-25End date
2020-11-27ISSN
0302-9743eISSN
1611-3349ISBN-13
9783030657444Publication classification
E1 Full written paper - refereedEditor/Contributor(s)
Miroslaw Kutylowski, Jun Zhang, Chao ChenTitle of proceedings
NSS 2020 : Proceedings of the 14th International Network and system Security ConferenceUsage metrics
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