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A Secure Privacy-Preserving Data Aggregation Scheme Based on Bilinear ElGamal Cryptosystem for Remote Health Monitoring Systems - 2017

A Secure Privacy-Preserving Data Aggregation Scheme Based on Bilinear ElGamal Cryptosystem for Remote Health Monitoring Systems

Research Area:  Wireless Sensor Networks

Abstract:

Due to advancements in the development of wireless medical sensing devices and wireless communication technologies, the wireless body area network (WBAN) has become an eminent part of e-healthcare systems. WBAN uses medical sensors to continuously monitor and collect the physiological parameters of a patients health and send them to a remote medical server through a portable digital assistance (PDA)/mobile. Due to limitations in communication, such as power, storage, and the computational capabilities of sensors, data aggregation techniques are used to reduce the communication overhead in real-time data transmission in WBAN. However, since the WBAN transmits sensitive health data, data security and data privacy are a major concern. In this paper, we propose a secure privacy-preserving data aggregation (SPPDA) scheme based on bilinear pairing for remote health monitoring systems to improve data aggregation efficiency and data privacy. Our proposed SPPDA scheme utilizes the homomorphic property of the bilinear ElGamal cryptosystem to perform privacy-preserving secure computation and combines it with the aggregate signature scheme, enabling data authenticity/integrity in the WBAN. The proposed SPPDA scheme is proved to be semantically secure under the decisional bilinear Diffie-Hellman assumption. Security analysis demonstrates that our proposed scheme preserves data confidentiality, data authenticity, and data privacy; it also resists passive eavesdropping and replay attacks. A performance evaluation based on simulation results and a comparison of computational cost with related schemes show that data aggregation and batch verification at the PDA significantly reduce communication and transmission overhead and support efficient computation at the remote server.

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Author(s) Name:  Anees Ara; Mznah Al-Rodhaan; Yuan Tian and Abdullah Al-Dhelaan

Journal name:  IEEE Access

Conferrence name:  

Publisher name:  IEEE

DOI:  10.1109/ACCESS.2017.2716439

Volume Information:  Volume: 5,Page(s): 12601 - 12617