Secure Range Search Over Encrypted Uncertain IoT Outsourced Data

Abstract

Internet of Things (IoT) is an increasingly popular technological trend. The operation of IoT needs a strong data-handling capacity, where most of the data are sensor data. Limitations associated with measurement, delays in data updating, and/or the need to preserve the privacy of data can result in the sensor data being uncertain. Thus, one key challenge is “how do we ensure the privacy of data collected from IoT devices, particularly uncertain data, that are being outsourced to the cloud for analysis, storage and archival?”. Searchable encryption scheme is a promising technique that allows the searching over encrypted (uncertain) data stored offshore. In this paper, we propose a secure range search for encrypted data from IoT devices. Specifically, we use homomorphic and order-preserving encryption to encrypt data published by the data owners. We then use the k-dimensional tree to build the data index. Our scheme is designed to ensure the privacy of the dataset, without affecting the efficiency of keyword search on the (encrypted) dataset. We also demonstrate that our scheme can preserve both data and query privacy, as well as evaluating its performance to demonstrate efficiency.