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Found 5 papers, 0 papers with code
Obscure: Information-Theoretically Secure, Oblivious, and Verifiable Aggregation Queries on Secret-Shared Outsourced Data -- Full Version
Despite exciting progress on cryptography, secure and efficient query processing over outsourced data remains an open challenge.
Quest: Practical and Oblivious Mitigation Strategies for COVID-19 using WiFi Datasets
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.
Panda: Partitioned Data Security on Outsourced Sensitive and Non-sensitive Data
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.
Concealer: SGX-based Secure, Volume Hiding, and Verifiable Processing of Spatial Time-Series Datasets
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.
Prism: Private Verifiable Set Computation over Multi-Owner Outsourced Databases
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.
