The Privacy Enhancing Common Social Features Discovery Project aims at providing mobile users the opportunity to discover common social features they may have with other (possibly stranger) users. In numerous applications, users need to make trust and/or access control decisions involving other (possibly stranger) users, and one important factor is often the existence of common social feature (e.g., friendship, interest, etc.). This motivates the need for secure, privacy-preserving and efficient techniques allowing users to assess whether or not they have mutual attributes. Main challenges involved in this project are:
- Exploration of social graph with data authenticity guarantees
- Secure distribution of explored data (see: PeerShare project)
- Discovery of common attributes by means of Private Set Intersection (PSI) protocols
Results
We have built a framework for privacy-preserving determination of common friends (or more generally distance between two nodes on the social graph). This framework can be used by mobile app developers. We have built two example applications.
Papers
- Marcin Nagy, Emiliano De Cristofaro, Alexandra Dmitrienko, N. Asokan, Ahmad-Reza Sadeghi: Do I Know You? – Efficient and Privacy-Preserving Common Friend-Finder Protocols and Applications ACSAC ’13 Proceedings of the 29th Annual Computer Security Applications Conference, December 2013
- Marcin Nagy, Thanh Bui, Emiliano De Cristofaro, N. Asokan, Jörg Ott, Ahmad-Reza Sadeghi: How far removed are you?: scalable privacy-preserving estimation of social path length with Social PaL WiSec’15 Proceedings of the 8th ACM Conference on Security & Privacy in Wireless and Mobile Networks, June 2015
- Marcin Nagy, Thanh Bui, Swapnil Udar, N. Asokan, Jörg Ott: SpotShare and nearbyPeople: Applications of the Social PaL Framework WiSec’15 Proceedings of the 8th ACM Conference on Security & Privacy in Wireless and Mobile Networks, June 2015
Technical reports
- Marcin Nagy, Emiliano De Cristofaro, Alexandra Dmitrienko, N. Asokan, Ahmad-Reza Sadeghi: Do I Know You? – Efficient and Privacy-Preserving Common Friend-Finder Protocols and Applications, September 2013
- Marcin Nagy, Thanh Bui, Emiliano De Cristofaro, N. Asokan, Jörg Ott, Ahmad-Reza Sadeghi: How Far Removed Are You? Scalable Privacy-Preserving Estimation of Social Path Length with Social PaL, December 2014
Presentations
- Efficient and Privacy-Preserving Common Friend-Finder Protocols and Applications, December 2013.
- How Far Removed Are You? Scalable Privacy-Preserving Estimation of Social Path Length with Social PaL, June 2015
- Social Path Lengths of People Nearby, June 2015