Abstract

Nowadays the healthcare system is undergoing a paradigm shift to integrate cloud computing and Internet-of-Things with physical medical equipments into a distributed network ensuring real-time and near real-time data transfer from the physical world to the cyber space for computation, storage and analysis. Namely, the healthcare system can be seen as a cyber–physical system (CPS) for patient-centric healthcare applications and services, called Health-CPS, based on cloud computing, Wireless Body Area Networks (WBANs) and big data analytics technologies. Health-CPS has played an important role in healthcare for improving treatment quality and patients’ assistance speed. However, despite these advantages, the development of Health-CPS will be restricted by serious security threats, especially the security threats to the healthcare-related data. Because Health-CPS forward Electronic health records (EHRs), biomedical signals of patients and public health to the cloud which may operate in distributed and hostile environments, novel security mechanisms are required to prevent malicious interactions to the storage infrastructure. Therefore, the cloud providers must take strong security measures to protect the integrity and privacy of the healthcare related data. But most of the researchers do not simultaneously pay attention to both integrity and privacy for Health-CPS. Therefore, we proposed a privacy-preserving data integrity verification model by using lightweight streaming authenticated data structures for Health-CPS. We have given the design idea, architecture, formal definition, security definition, communication protocols of our model in detail. The key construction processes of our model which include initialization, data appending, scale expansion, data query and verification, are also given in this paper. Finally, the security and performance analysis show that our scheme is not only secure but also efficient.

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