Aggregation Tree Statistical Computing Based on Functional Encryption

The medical monitoring system is widely used. In the medical monitoring system, each user only possesses one piece of data logging that participates in statistical computing. Specifically in such a situation, a feasible solution is to scatter its statistical computing workload to corresponding statistical nodes. Moreover, there are still two problems that should be resolved. One is how the server takes advantage of intermediate results obtained through statistical node aggregation to perform statistical computing. Statistical variable decomposition technique points out the direction for statistical projects. The other problem is how to design an efficient topological structure for statistical computing. In this paper, tree topology was adopted to implement data aggregation to improve aggregation efficiency. And two experiments were done for time consumption of statistical computing which focuses on encrypted data aggregation and encrypted data computing. The first experiment indicates that encrypted data aggregation efficiency of the scheme proposed in this paper is better than that of Drosatos’ scheme, and the second indicates that improving computing power of the server or computational efficiency of the functional encryption scheme can shorten the computation time.