skip to main content

Search for: All records

Award ID contains: 1651230

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Augmented reality (AR), which overlays virtual content on top of the user’s perception of the real world, has now begun to enter the consumer market. Besides smartphone platforms, early-stage head-mounted displays such as the Microsoft HoloLens are under active development. Many compelling uses of these technologies are multi-user: e.g., inperson collaborative tools, multiplayer gaming, and telepresence. While prior work on AR security and privacy has studied potential risks from AR applications, new risks will also arise among multiple human users. In this work, we explore the challenges that arise in designing secure and private content sharing for multi-user AR. We analyze representative application case studies and systematize design goals for security and functionality that a multi-user AR platform should support. We design an AR content sharing control module that achieves these goals and build a prototype implementation (ShareAR) for the HoloLens. This work builds foundations for secure and private multi-user AR interactions.
  2. Augmented reality (AR) technologies, such as Microsoft’s HoloLens head-mounted display and AR-enabled car windshields, are rapidly emerging. AR applications provide users with immersive virtual experiences by capturing input from a user’s surroundings and overlaying virtual output on the user’s perception of the real world. These applications enable users to interact with and perceive virtual content in fundamentally new ways. However, the immersive nature of AR applications raises serious security and privacy concerns. Prior work has focused primarily on input privacy risks stemming from applications with unrestricted access to sensor data. However, the risks associated with malicious or buggy AR output remain largely unexplored. For example, an AR windshield application could intentionally or accidentally obscure oncoming vehicles or safety-critical output of other AR applications. In this work, we address the fundamental challenge of securing AR output in the face of malicious or buggy applications. We design, prototype, and evaluate Arya, an AR platform that controls application output according to policies specified in a constrained yet expressive policy framework. In doing so, we identify and overcome numerous challenges in securing AR output.