A novel model for preserving Location Privacy in Internet of Things

Abstract

The Internet of Things (IoT) is an Internet-based architecture for the exchange of information and services amongst millions of devices. Due to massive use of IoT for various benefits, there are high security and privacy related issues which need to be addressed. Many techniques have been proposed for preserving location privacy in the context of IoT. Some of these techniques are based on anonymization and others on obfuscation. However, the existing research clearly lags in preserving location privacy in IoT and has common issues such as being specific or restricted to certain location. This research focuses on preserving location privacy in the context of IoT. In this paper, we propose an Enhanced Semantic Obfuscation Technique (ESOT) for preserving location privacy in the IoT. We compare the performance of ESOT with previously developed Semantic Obfuscation Technique (SOT). The results show that ESOT achieves better location privacy and provides a balance between privacy and utility of location services.