Securing location privacy in Augmented Reality

Abstract

In Augmented Reality (AR), users main concern includes privacy and safety of data. Since location based services (LBS) are one of the major applications of the AR, it is important to have a privacy-aware management of location information, providing location privacy for clients against vulnerabilities or abuse. This paper discusses how to protect the location privacy from various privacy threats, which occurred because of the unlimited usage of LBS, by a scalable architecture. We have developed an efficient LBS privacy protection algorithm. In our model, k-anonymization and pseudo-anonymization methods are used hand in hand. The proposed location privacy frame work is implemented by an efficient trusted third party server. We have studied the efficiency of our algorithm under different conditions using realistic work loads. Our experiment shows that the k-anonymization and the pseudo-anonymization methods used together in our algorithm provide an efficient location privacy.