Privacy-Preserving and Efficient Range Counting in IoT Networks

In recent years, Internet of Things (IoT) networks have been received much attention due to their intelligence and automation. Numerous devices are deployed in the networks, and many applications are willing to obtain the distribution of IoT devices in one range for data analysis. However, some distributions of IoT devices include sensitive information which may disclose the privacy of their owners. And most IoT devices cannot afford heavy computation because of their low computing power and limited storage capacity. In this paper, we propose a privacy-preserving and efficient scheme that satisfies local differential privacy and supports O(1) -time-complexity range counting query which can find the number of IoT devices in a range. It also allows IoT devices to join or exit dynamically. Finally, theoretical analysis proves that our scheme satisfies local differential privacy, and our experiments show that our range counting query scheme can get the microsecond level.