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APPA: An anonymous and privacy preserving data aggregation scheme for fog-enhanced IoT - 2019

APPA: An anonymous and privacy preserving data aggregation scheme for fog-enhanced IoT

Research Area:  Fog Computing

Abstract:

Fog computing is a modern computing platform that connects the cloud with the edge smart devices located at the edge of the network. The fog computing platform has several characteristics desirable for Internet of Things (IoT) systems, such as the efficient data access, low latency, and location awareness. Data aggregation is a common operation in IoT systems. However, for data aggregation applications in the fog-enhanced IoT environment, how to efficiently preserve the privacy of sensitive data is a major concern. To address this challenge, we propose APPA: a device-oriented Anonymous Privacy-Preserving scheme with Authentication for data aggregation applications in fog-enhanced IoT systems, which also supports multi-authority to manage smart devices and fog nodes locally. In APPA scheme, the anonymity and authenticity of the device is guaranteed with pseudonym and pseudonym certificate, which can be updated autonomously. Taking the advantage of a local certification authority, the pseudonym management can be shifted to specialized fogs at the network edge, which provide real-time service for device registration and update. The data privacy can be ensured during data aggregation by using the Paillier algorithm. Detailed security analysis is conducted to show that our scheme can achieve security and privacy-preservation properties in the fog-enhanced IoT systems. Additionally, we compare our scheme with existing schemes to demonstrate the effectiveness and efficiency of our proposed scheme in terms of low computational complexity and communication overhead.

Keywords:  

Author(s) Name:  Zhitao Guan,Yue Zhang,Long and others

Journal name:  Journal of Network and Computer Applications

Conferrence name:  

Publisher name:  Elsevier

DOI:  https://doi.org/10.1016/j.jnca.2018.09.019

Volume Information:  Volume 125, 1 January 2019, Pages 82-92