Secure and Lightweight Data Aggregation Scheme for Anonymous Multi-Receivers in WBAN

Abstract

Wireless body area networks (WBANs) provide healthcare providers with early warning of medical emergencies by monitoring vital parameters of a patient's body with wearable devices embedded with biosensors. However, the resource-constrained nature of WBAN devices makes the data collected from them vulnerable to internal and external attacks during transmission. By aggregating medical data, data aggregation technology is used to conduct statistical analysis of the data and achieve confidentiality of patient information, which can help doctors make the correct diagnosis and assist medical insurance companies choose the right insurance for patients. However, the existing data aggregation schemes are inefficient or prone to potential safety risks to patients due to their high computational intensity and known identity of recipients. To address it, we propose a privacy-preserving health data aggregation scheme in the multi-receiver setting, which not only securely collects health data from IoT wearable devices but also supports the anonymity of multiple receivers while avoiding time-consuming pairing operations. Since the patient's health data and the recipient's identities are transmitted in cipher-text, it effectively prevents data leakage and achieves privacy protection of identity information among recipients. Compared with several existing schemes, the proposed scheme not only achieves anonymity of the collected data and the receivers' identities,but also makes it lightweight. Furthermore, experimental results demonstrate that the proposed scheme is cost-efficient in an all-around performance.