This paper proposes Prism, a secret sharing based approach to compute private set operations (i. e., intersection and union), as well as aggregates over outsourced databases belonging to multiple owners.
This paper proposes a system, entitled Concealer that allows sharing time-varying spatial data (e. g., as produced by sensors) in encrypted form to an untrusted third-party service provider to provide location-based applications (involving aggregation queries over selected regions over time windows) to users.
We, first, provide a new security definition, entitled partitioned data security for guaranteeing that the joint processing of non-sensitive data (in cleartext) and sensitive data (in encrypted form) does not lead to any leakage.
In this paper, we introduce Quest, a system that empowers organizations to observe individuals and spaces to implement policies for social distancing and contact tracing using WiFi connectivity data in a passive and privacy-preserving manner.
Despite exciting progress on cryptography, secure and efficient query processing over outsourced data remains an open challenge.