An efficient and privacy-preserving data aggregation scheme supporting arbitrary statistical functions in IoT

Abstract

The Internet of Things (IoT) has profoundly impacted our lives and has greatly revolutionized our lifestyle. The terminal devices in an IoT data aggregation application sense real-time data for the remote cloud server to achieve intelligent decisions. However, the high frequency of collecting user data will raise people concerns about personal privacy. In recent years, many privacy-preserving data aggregation schemes have been proposed. Unfortunately, most existing schemes cannot support either arbitrary aggregation functions, or dynamic user group management, or fault tolerance. In this paper, we propose an efficient and privacy-preserving data aggregation scheme. In the scheme, we design a lightweight encryption method to protect the user privacy by using a ring topology and a random location sequence. On this basis, the proposed scheme supports not only arbitrary aggregation functions, but also flexible dynamic user management. Furthermore, the scheme achieves fault-tolerant capabilities by utilizing a future data buffering mechanism. Security analysis reveals that the scheme can achieve the desired security properties, and experimental evaluation results show the scheme's efficiency in terms of computational and communication overhead.