A Scanner Darkly: Protecting User Privacy from Perceptual Applications
Perceptual, "context-aware" applications that observe their surroundings and interact with users via cameras and other sensors are becoming ubiquitous on personal computers, mobile phones, gaming platforms, household robots, and augmented-reality devices. Their ability to collect fine-grained images of their environment raises unique, interesting privacy risks for their users.
This talk will describe the design and implementation of Darkly, a practical privacy protection system for the increasingly common scenario where an untrusted, third-party perceptual application is running on a trusted device. Darkly is seamlessly integrated with OpenCV, a popular computer vision library used by such applications to access perceptual inputs. It deploys multiple privacy protection mechanisms including access control, algorithmic privacy transforms, and user audit.
This is joint work with Suman Jana and Arvind Narayanan.