We focus on a scenario in which a single company wishes to obtain the distribution of aggregate features, while ensuring a high level of privacy for the users. We are interested in the case where users own devices that are not necessarily powerful or online at all times, like smartphones or web browsers. This premise makes general solutions, such as general multiparty computation (MPC), less applicable.
We design an efficient special-purpose MPC protocol that outputs aggregate features to the company, while keeping online presence and computational complexity on the users’ side at a minimum. This basic protocol is secure against a majority of corrupt users, as long as they do not collude with the company. If they do, we still guarantee security, as long as the fraction of corrupt users is lower than a certain, tweakable, parameter. We propose different enhancements of this solution: one guaranteeing some degree of active security, and one that additionally ensures differential privacy.
Finally, we report on the performance of our implementation on several realistic real-world use-cases across different devices.
Category / Keywords: applications / multi-party computation, privacy, mobile Date: received 29 Jun 2017 Contact author: mortendahlcs at gmail com Available format(s): PDF | BibTeX Citation Version: 20170705:211549 (All versions of this report) Short URL: ia.cr/2017/643 Discussion forum: Show discussion | Start new discussion