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SMCQL: Secure Querying for Federated Databases
TLDR
This work proposes the Private Data Network, a federated database for querying over the collective data of mutually distrustful parties, and introduces a framework for executing PDN queries named SMCQL, which translates SQL statements into SMC primitives to compute query results over the union of its source databases. Expand
ShrinkWrap: Efficient SQL Query Processing in Differentially Private Data Federations
TLDR
Shrinkwrap is introduced, a private data federation that offers data owners a differentially private view of the data held by others to improve their performance over oblivious query processing and provides a trade-off between result accuracy and query evaluation performance. Expand
SMCQL: Secure Query Processing for Private Data Networks
TLDR
This work proposes a novel generalization of federated database systems called a private data network (PDN), and it is designed for querying over the collective data of mutually distrustful parties, and is preparing SMCQL for an open-source release. Expand
Shrinkwrap: Differentially-Private Query Processing in Private Data Federations
TLDR
Shrinkwrap is introduced, a private data federation that offers data owners a differentially private view of the data held by others to improve their performance over oblivious query processing and provides a trade-off between result accuracy and query evaluation performance. Expand
SAQE: Practical Privacy-Preserving Approximate Query Processing for Data Federations
TLDR
SAQE, the Secure Approximate Query Evaluator, a private data federation system that scales to very large datasets by combining three techniques — differential privacy, secure computation, and approximate query processing — in a novel and principled way is proposed. Expand
Privacy Changes Everything
TLDR
It is argued that there is an urgent need for trustworthy database system that offer end-to-end privacy guarantees for their records with user interfaces that closely resemble that of a relational database. Expand
Practical Security and Privacy for Database Systems
TLDR
This tutorial will first describe the security and privacy requirements for database systems in different settings and cover the state-of-the-art tools that achieve these requirements and show challenges in integrating these techniques together. Expand
Prior-Aware Distribution Estimation for Differential Privacy
TLDR
This work examines the joint distribution estimation problem given two data points: 1) differentially private answers of a workload computed over private data and 2) a prior empirical distribution from a public dataset and proposes an approach based on iterative optimization for solving this problem. Expand
Poirot: private contact summary aggregation: poster abstract
TLDR
A preliminary evaluation of the Poirot system is shown, a system to collect aggregate statistics about physical interactions in a privacy-preserving manner, that demonstrates the scalability of the approach even while maintaining strong privacy guarantees. Expand
DP-Sync: Hiding Update Patterns in Secure Outsourced Databases with Differential Privacy
TLDR
A novel secure outsourced database framework for growing data, DP-Sync, which interoperate with a large class of existing encrypted databases and supports efficient updates while providing differentially-private guarantees for any single update. Expand
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