PMDP: A Framework for Preserving Multiparty Data Privacy in Cloud Computing
Joint Authors
Wei, Jianghong
Hu, Xuexian
Li, Ji
Liu, Wenfen
Source
Security and Communication Networks
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-12
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Information Technology and Computer Science
Abstract EN
The amount of Internet data is significantly increasing due to the development of network technology, inducing the appearance of big data.
Experiments have shown that deep mining and analysis on large datasets would introduce great benefits.
Although cloud computing supports data analysis in an outsourced and cost-effective way, it brings serious privacy issues when sending the original data to cloud servers.
Meanwhile, the returned analysis result suffers from malicious inference attacks and also discloses user privacy.
In this paper, to conquer the above privacy issues, we propose a general framework for Preserving Multiparty Data Privacy (PMDP for short) in cloud computing.
The PMDP framework can protect numeric data computing and publishing with the assistance of untrusted cloud servers and achieve delegation of storage simultaneously.
Our framework is built upon several cryptography primitives (e.g., secure multiparty computation) and differential privacy mechanism, which guarantees its security against semihonest participants without collusion.
We further instantiate PMDP with specific algorithms and demonstrate its security, efficiency, and advantages by presenting security analysis and performance discussion.
Moreover, we propose a security enhanced framework sPMDP to resist malicious inside participants and outside adversaries.
We illustrate that both PMDP and sPMDP are reliable and scale well and thus are desirable for practical applications.
American Psychological Association (APA)
Li, Ji& Wei, Jianghong& Liu, Wenfen& Hu, Xuexian. 2017. PMDP: A Framework for Preserving Multiparty Data Privacy in Cloud Computing. Security and Communication Networks،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1203020
Modern Language Association (MLA)
Li, Ji…[et al.]. PMDP: A Framework for Preserving Multiparty Data Privacy in Cloud Computing. Security and Communication Networks No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1203020
American Medical Association (AMA)
Li, Ji& Wei, Jianghong& Liu, Wenfen& Hu, Xuexian. PMDP: A Framework for Preserving Multiparty Data Privacy in Cloud Computing. Security and Communication Networks. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1203020
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1203020