Multi-Dimensional Flat Indexing for Encrypted Data
Sabrina De Capitani di Vimercati, Dario Facchinetti, Sara Foresti, Gianluca Oldani, Stefano Paraboschi, Matthew Rossi, Pierangela Samarati
In IEEE Transactions on Cloud Computing (TCC)
We address the problem of indexing encrypted data outsourced to an external cloud server to support server-side execution of multi-attribute queries. Our approach partitions the dataset in groups with the same number of tuples, and associates all tuples in a group with the same combination of index values, so to guarantee protection against static inferences. Our indexing approach does not require any modifications to the server-side software stack, and requires limited storage at the client for query support. The experimental evaluation considers, for the storage of the encrypted and indexed dataset, both a relational database (PostgreSQL) and a key-value database (Redis). We carried out extensive experiments evaluating client-storage requirements and query performance. The experimental results confirm the efficiency of our solution. The proposal is supported by an open source implementation.
@article{flat-index,
author={De Capitani di Vimercati, Sabrina and Facchinetti, Dario and Foresti, Sara and Oldani, Gianluca and Paraboschi, Stefano and Rossi, Matthew and Samarati, Pierangela},
journal={IEEE Transactions on Cloud Computing},
title={Multi-Dimensional Flat Indexing for Encrypted Data},
year={2024},
volume={},
number={},
pages={1-14},
keywords={Indexing;Servers;Cloud computing;Protection;Encryption;Outsourcing;Time-frequency analysis;Data outsourcing;efficient query execution;encrypted data;multi-dimensional index},
doi={10.1109/TCC.2024.3408905}
}