DynaPro: Dynamic Wireless Sensor Network Data Protection Algorithm in IoT via Differential Privacy

Abstract

With the advent of the era of intelligent Internet of Things (IoT), more and more personal information are collected in the process of deploying IoT in various domains. This brings the problem of data protection in IoT. To address this problem, we propose a data protection algorithm, called DynaPro, based on differential privacy for dynamic wireless sensor networks (WSN), which is the sensor layer of IoT. DynaPro has addressed two issues in data protection of wireless sensor networks. The first issue is the dynamic topology of the network. In order to solve this problem, DynaPro has adopted methods like time window, hierarchical sampling, and graph similarity to process the snapshots of the dynamic network topology. The second issue is addition of noise in differential privacy. To address this issue, DynaPro uses Hierarchical Random Graph (HRG) as middleware to apply differential privacy protection. Instead of adding noise to network data and topology directly, DynaPro adds noise to HRG. In this way, DynaPro can hide the network topology but retain the necessary structural information to support data analysis. Theoretical analysis and experimental results show that DynaPro can preserve the important network features of the original network topology under the premise of the differential privacy protection model.