A homomorphic range-searching scheme for sensitive data in the internet of things

Abstract

With the popularisation and development of the internet of things, big data and cloud computing, the search of data in cloud-based internet of things becomes a hot research topic. However, the sensitive data, such as the medical data collected by wearable devices, is inevitable to be stored in the cloud server. Homomorphic encryption has the ability to calculate the ciphertext without decryption. We separate the calculating and the decryption into different security domains to preserve the privacy of sensitive data, so the original plaintext would not be exposed in the cloud. Hence, we can compare two ciphertexts to get the difference of them in a privacy preserving way. In order to accelerate the search process of range query, we build an encrypted self-balancing binary index tree. Based on oblivious RAM, the searching scheme can hide the access patterns of the node of tree. The actual nodes and logic relation of tree are stored on different servers. A sample implementation of the proposed scheme is given, and the experimental results and analysis are presented to illustrate the scheme's effectiveness and security.