Cloud‐based privacy‐preserving aggregation architecture in multi‐domain wireless networks. Issue 13 (17th January 2014)

• Record Type: Journal Article
• Authors: Jia, Weiwei; Zhu, Haojin; Du, Suguo; Dong, Xiaolei; Cao, Zhenfu
• Is Part Of: Security and communication networks. Volume 9:Issue 13(2016)
• Page Start: 1905
• Page End: 1915
• Publication Date: 2014-01-17
• Subjects: privacy aggregation -- cloud computing -- participatory sensing; Computer networks -- Security measures -- Periodicals; Computer security -- Periodicals; Cryptography -- Periodicals; 005.805
• DOI: 10.1002/sec.950
• Languages: English
• ISSNs: 1939-0114

Abstract

Abstract: Enabling privacy preserving outsourced data aggregation is regarded as an important issue for multi‐domain wireless networks. In this paper, we present a novel hybrid cloud‐based privacy‐preserving outsourced data aggregation framework. To achieve this, we introduce a hybrid storage cloud and aggregator cloud architecture, in which both of the storage clouds and aggregator cloud are assumed to be untrusted. On the basis of this security assumption, we firstly propose two novel basic protocols, including the proactive privacy‐preserving aggregation and reactive privacy‐preserving aggregation schemes, which are based on the idea of secret sharing. The proactive scheme allows the user to proactively split their data to multiple storage clouds to avoid data leaking while the reactive scheme allows the users to store their encrypted data in storage cloud and aggregator to finish the data aggregation based on the encrypted data. Moreover, on the basis of the proactive privacy‐preserving data aggregation and reactive privacy‐preserving data aggregation, we further propose an advanced protocol, which can resist the malicious data mining attack. The detailed performance simulations are given to demonstrate the security, effectiveness, and efficiency of the proposed scheme. Copyright © 2014 John Wiley & Sons, Ltd. Abstract : In this paper, we present a novel hybrid cloud‐based privacy‐preserving outsourced data aggregation framework. Under this framework, we present the protocols to realize the privacy‐preserving aggregation and resist the malicious data mining attack. The detailed performance simulations are given to demonstrate the security, effectiveness, and efficiency of the proposed protocols.