Title
IncShrink: Architecting Efficient Outsourced Databases using Incremental MPC and Differential Privacy
Abstract
In this paper, we consider secure outsourced growing databases (SOGDB) that support view-based query answering. These databases allow untrusted servers to privately maintain a materialized view. This allows servers to use only the materialized view for query processing instead of accessing the original data from which the view was derived. To tackle this, we devise a novel view-based SOGDB framework, IncShrink. The key features of this solution are: (i) IncShrink maintains the view using incremental MPC operators which eliminates the need for a trusted third party upfront, and (ii) to ensure high performance, IncShrink guarantees that the leakage satisfies DP in the presence of updates. To the best of our knowledge, there are no existing systems that have these properties. We demonstrate IncShrink's practical feasibility in terms of efficiency and accuracy with extensive experiments on real-world datasets and the TPC-ds benchmark. The evaluation results show that IncShrink provides a 3-way trade-off in terms of privacy, accuracy and efficiency, and offers at least a 7,800x performance advantage over standard SOGDB that do not support view-based query paradigm.
Year
DOI
Venue
2022
10.1145/3514221.3526151
PROCEEDINGS OF THE 2022 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA (SIGMOD '22)
Keywords
DocType
ISSN
Incremental MPC, Differential privacy, Secure outsourced database
Conference
0730-8078
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Chenghong Wang1549.71
Johes Bater201.35
Kartik Nayak31859.20
Ashwin Machanavajjhala42624132.52