The ubiquity of portable mobile cameras have led to a transformation in how and when digital images are captured, shared, and archived. Photographs and videos from social gatherings, public events, and even crime scenes are commonplace online. While the spontaneity afforded by these devices have led to new personal and creative outlets, privacy concerns of bystanders (and indeed, in some cases, unwilling subjects) have remained largely unaddressed. We present I-Pic, a trusted software platform that integrates digital capture with user-defined privacy.
I-Pic: A Platform for Privacy-Compliant Image Capture
[Paper] [BibTex] [Video]
Paarijaat Aditya, Rijurekha Sen, Seong Joon Oh, Rodrigo Benenson, Bobby Bhattacharjee, Peter Druschel, Tong Tong Wu, Mario Fritz and Bernt Schiele
To Appear in 14th International Conference on Mobile Systems, Applications, and Services (MobiSys '16), June 2016.
In I-Pic, users choose a level of privacy (e.g., image capture allowed or not) based upon social context (e.g., out in public vs. with friends vs. at workplace). Privacy choices of nearby users are advertised via short-range radio (Bluetooth Low Energy), and I-Pic-compliant capture platforms generate edited media to conform to privacy choices of image subjects.
I-Pic uses secure multiparty computation to ensure that users’ visual features and privacy choices are not revealed publicly, regardless of whether they are the subjects of an image capture. Just as importantly, I-Pic preserves the ease-of-use and spontaneous nature of capture and sharing between trusted users. Our evaluation of I-Pic shows that a practical, energy-efficient system that conforms to the privacy choices of many users within a scene can be built and deployed using current hardware.
| Max Planck Institute for Software Systems (MPI-SWS) | |
|---|---|
 |
|
| Max Planck Institute for Informatics (MPI-INF) | |
 |
|
| University of Maryland | |
 |
|
| University of Rochester | |
 |
|