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Secure and efficient data aggregation for IoT monitoring systems

Rezaeibagha, F., Mu, Y., Huang, K. and Chen, L. (2020) Secure and efficient data aggregation for IoT monitoring systems. IEEE Internet of Things Journal . Early Access.

Link to Published Version: https://doi.org/10.1109/JIOT.2020.3042204
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Abstract

The proliferation of Internet of Things (IoT) as a promising paradigm has contributed enormously to modern technology design. The wireless body sensor network (WBSN) technology is an application of IoT in healthcare, whereas data security and privacy impediments have raised some concerns. The collected data via IoT wireless body sensors is vulnerable to a variety of internal and external attacks. One solution is to encrypt or sign the collected data to provide confidentiality and integrity, but the computational complexity hinders the application in the real IoT-based healthcare devices. Although there have been some attempts to provide secure and efficient IoT schemes, there is a lack of achieving secure data analysis in modern healthcare. The aggregated data statistics about the patient’s medical status is useful to doctors and healthcare providers. However, the dynamic data continually updating over time is challenging. In this paper, we present an efficient and provably secure scheme, which is the first step towards secure data analysis for handling the data collection and analysis for IoT wireless body sensors. The main contribution of our work is a novel cryptographic accumulator based on our novel authenticated additive homomorphic encryption which can collect and accumulate data from IoT wireless wearable devices. These encrypted data can be used for analysis in an encrypted form so that the information is not revealed. To validate security and efficiency, we present security analysis and performance evaluations of our proposed scheme for IoT wireless body sensors.

Item Type: Journal Article
Murdoch Affiliation(s): Information Technology, Mathematics and Statistics
Publisher: IEEE
Copyright: © 2021 IEEE
URI: http://researchrepository.murdoch.edu.au/id/eprint/59194
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