Understand and Measure Privacy

Cameras are now pervasive on consumer devices, including smartphones, laptops, tablets, and new wearable devices like Google Glass and the Narrative Clip lifelogging camera.

This project addresses several key emerging security challenges that arise due to the wildly successful large-scale adoption of mobile devices with diverse network capabilities. The novel approach focuses on to understanding how various information that are legitimately and willingly provided by smartphone users due to the requested permissions of downloaded applications can be potentially abused. The second research focus is to identify improvements in the design of cellular network middlebox (e.g., firewall) policies by detailed exposure and explicitly defining the key requirements.

This research project studies security and privacy for wearable devices. Wearable computing is poised to become widely deployed throughout society. These devices offer many benefits to end users in terms of realtime access to information and the augmentation of human memory, but they are also likely to introduce new and complex privacy and security problems. People who use wearable devices need assurances that their privacy will be respected, and we also need ways to minimize the potential for wearable devices to intrude on the privacy of bystanders and others.

This research is focused on the creation of new techniques and algorithms to support comprehensive analysis of Android applications. We have developed formally grounded techniques for extracting accurate models of smartphone applications from installation images. The recovery formalization is based on TyDe, a typed meta-representation of Dalvik bytecode (the code structure used by the Android smartphone operating system).

Most of the world's internet access occurs through mobile devices such as smart phones and tablets. While these devices are convenient, they also enable crimes that intersect the physical world and cyberspace. For example, a thief who steals a smartphone can gain access to a person's sensitive email, or someone using a banking app on the train may reveal account numbers to someone looking over her shoulder. This research will study how, when, and where people use smartphones and the relationship between these usage patterns and the likelihood of being a victim of cybercrime.