ARSpy: Groundbreaking Multi-Player Augmented Reality Application for Tracking User Location PROJECT TITLE : ARSpy: Breaking Location-Based Multi-Player Augmented Reality Application for User Location Tracking ABSTRACT: Augmented reality (AR) applications, which combine a user's perception of the real world with information that is digitally generated, are on the verge of becoming viable from a business perspective. There are now a number of commercial platforms that support augmented reality, such as smartphones and Microsoft HoloLens. They provide a supplement to the user's normal 3D world and extend the user experience beyond the conventional two dimensions. The operation of a typical location-based multi-player augmented reality application takes place through a three-step process. First, the system collects sensory data from the real world. Next, it identifies objects based on the context in which they are located. Finally, the system renders information on top of the user's senses. Nevertheless, due to the fact that these augmented reality applications frequently exchange data with users, they have brought about new concerns regarding individual and public safety. In this paper, we develop ARSpy, a user location tracking system that is solely based on network traffic information of the user, and we test it on location-based multi-player augmented reality applications. ARSpy was based on network traffic information of the user. We show that we are able to obtain the geolocation of any target with a high level of accuracy by conducting real-world experiments on 12 volunteers. These experiments allow us to demonstrate the efficacy and efficiency of the proposed scheme. As a further measure against these side channel attacks, we propose three different preventative measures. Our findings highlight a potential security risk in the currently available location-based multi-player augmented reality applications and serve as an important security reminder to a large number of users of AR technology. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Walking Direction Estimation and Attention-Based Gait Recognition in Wi-Fi Networks App Popularity Prediction Using Time-Varying Hierarchical Interactions