可验证医疗密态数据聚合与统计分析方案

随着移动通信网络的飞速发展，越来越多的可穿戴设备通过移动终端接入网络并上传大量医疗数据，这些医疗数据聚合后具有重要的医学统计分析与决策价值.然而，在医疗数据传输和聚合过程中会出现传输中断、信息泄露、数据篡改等问题.为了解决这些安全与隐私问题，同时支持高效而正确的医疗密态数据聚合与统计分析功能，提出了基于移动边缘服务计算的具有容错机制的可验证医疗密态数据聚合方案.该方案改进了BGN同态加密算法，并结合Shamir秘密共享机制，确保医疗数据机密性、密态数据的可容错聚合.该方案提出了移动边缘服务计算辅助无线体域网的概念，结合移动边缘计算和云计算，实现海量医疗大数据实时处理与统计分析.该方案通过边缘计算服务器和云服务器两层聚合，提高聚合效率，降低通信开销.同时，使用聚合签名技术实现医疗密态数据的批量验证功能，进而保障其在传输与存储过程中的完整性.性能比较与分析表明，该方案在计算与通信开销方面都具备突出优势.

Verifiable Encrypted Medical Data Aggregation and Statistical Analysis Scheme

Due to the fast development of mobile communication networks, more and more wearable devices access the network through mobile terminals and produce massive data. These aggregated medical data have significant statistical analysis and decision making value. Nevertheless, there are emerge security and privacy issues (e.g., as transmission interruption, information leakage, and data tampering) in medical data transmission and aggregation process. To address those security issues and ensure accurate medical data aggregation and analysis, an efficient verifiable fault-tolerant medical data aggregation scheme is proposed based on mobile edge service computing. The scheme exploits a modified BGN homomorphic encryption algorithm, integrates Shamir secret sharing mechanism to ensure medical data confidentiality, fault tolerance of encrypted aggregated data, simultaneously. The concept of mobile edge-assisted service computing in wireless body area networks is proposed in the scheme. Combined with the advantages of mobile edge computing and cloud computing, the real-time big data processing and statistical analysis of massive medical big data could be conducted. Through edge-level aggregation and cloud-level aggregation, the aggregation efficiency is improved and the communication overhead is reduced. Besides, the scheme designs an aggregate signature algorithm to conduct batch verification on medical encrypted data, and guarantee the integrity during transmission and storage process. The comprehensive performance evaluation demonstrates that the proposed scheme has outstanding advantages in terms of computational costs and communication overhead.