Toward Efficient, Privacy-Aware Media Classification on Public Databases

TitleToward Efficient, Privacy-Aware Media Classification on Public Databases
Publication TypeConference Paper
Year of Publication2014
AuthorsFanti, G., Finiasz M., Friedland G., & Ramchandran K.
Other Numbers3800

The ability to search databases by providing multimedia examples of voices, faces, or locations instead of textual descriptions can be tremendously useful. At the same time, uploading media for queries---especially media that contains sensitive content---means sharing private information with a potentially untrusted service provider. The growing field of privacy-preserving database searches attempts to resolve this tension. Within this scope of private searches, private media classification and retrieval is particularly challenging due to the inherent inexactness of recognition; to be useful, image or other media classification systems must identify approximate matches rather than just exact ones. This is difficult to reconcile with distortion-intolerant and resource-heavy privacy primitives, especially in web-scale databases. In this paper, we present an architecture for media classification on public databases that preserves client privacy while achieving asymptotic communication and computation costs that are sublinear in the size of the database. We demonstrate the usefulness of this architecture in the context of a privacy-preserving face recognition system. We observe order-of-magnitude speedups over state-of-the-art private face recognition systems.


This work is supported by the Intelligence Advanced ResearchProjects Activity (IARPA) via Department of Interior National Business Center contract number D11PC20071. The U.S. Governmentis authorized to reproduce and distribute reprints for Governmentalpurposes not withstanding any copyright annotation thereon. Dis-claimer: The views and conclusions contained herein are those ofthe authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of IARPA, DoI/NBC, or the U.S. Government.

Bibliographic Notes

Proceedings of International Conference on Multimedia Retrieval (ICMR '14), Glasgow, Scotland, pp. 49-56

Abbreviated Authors

G. Fanti, M. Finiasz, G. Friedland, and K. Ramchandran

ICSI Research Group

Audio and Multimedia

ICSI Publication Type

Article in conference proceedings