Privacy-Preserving Data Communication Through Secure Multi-Party Computation in Healthcare Sensor Cloud

In recent years, wireless medical sensor networks meet the web to enable exciting healthcare applications that require data communication over the Internet. Often these applications suffer from data disclosure due to malicious users' activities. To prevent such data disclosure in the healthcare systems, many public key cryptographic techniques have been used. However, most of them are too expensive to implement in the web-enabled wireless medical sensor networks. In 2013, Xun et al. introduced a lightweight encryption algorithm to protect communication between the sensor node and the data servers. Their scheme is based on the Sharemind framework. However, Sharemind framework has a limitation on the number of data storage servers (ie., three servers only). In addition, Xun et al's scheme does not support privacy-preserving patient data analysis for distributed databases of different hospitals. In this paper, we introduce a new practical approach to prevent data disclosure from inside attack. Our new proposal is based on FairplayMP framework which enables programmers who are not experts in the theory of secure computation to implement such protocols. In addition, it support any number of n participants and is suitable for distributed environments. Moreover, in our new scheme, each sensor node needs only one secret key stored in advance to communicate with n different data servers, whereas three secret keys are embedded in advance into each sensor in order to communicate with three data servers in Xun et al's scheme.