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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 Gao
With 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

12570

Series

Lecture Notes in Computer Science

Pagination

408 - 418

Publisher

Springer

Location

Melbourne, Australia

Place of publication

Berlin, Germany

Start date

2020-11-25

End date

2020-11-27

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783030657444

Publication classification

E1 Full written paper - refereed

Editor/Contributor(s)

Miroslaw Kutylowski, Jun Zhang, Chao Chen

Title of proceedings

NSS 2020 : Proceedings of the 14th International Network and system Security Conference