[Resource Topic] 2024/573: Tokenised Multi-client Provisioning for Dynamic Searchable Encryption with Forward and Backward Privacy

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Title:
Tokenised Multi-client Provisioning for Dynamic Searchable Encryption with Forward and Backward Privacy

Authors: Arnab Bag, Sikhar Patranabis, Debdeep Mukhopadhyay

Abstract:

Searchable Symmetric Encryption (SSE) has opened up an attractive avenue for privacy-preserved processing of outsourced data on the untrusted cloud infrastructure. SSE aims to support efficient Boolean query processing with optimal storage and search overhead over large real databases. However, current constructions in the literature lack the support for multi-client search and dynamic updates to the encrypted databases, which are essential requirements for the widespread deployment of SSE on real cloud infrastructures. Trivially extending a state-of-the-art single client dynamic construction, such as ODXT (Patranabis et al., NDSS’21), incurs significant leakage that renders such extension insecure in practice. Currently, no SSE construction in the literature offers efficient multi-client query processing and search with dynamic updates over large real databases while maintaining a benign leakage profile.
This work presents the first dynamic multi-client SSE scheme Nomos supporting efficient multi-client conjunctive Boolean queries over an encrypted database. Precisely, Nomos is a multi-reader-single-writer construction that allows only the gate-keeper (or the data-owner) - a trusted entity in the Nomos framework, to update the encrypted database stored on the adversarial server. Nomos achieves forward and type-II backward privacy of dynamic SSE constructions while incurring lesser leakage than the trivial extension of ODXT to a multi- client setting. Furthermore, our construction is practically efficient and scalable - attaining linear encrypted storage and sublinear search overhead for conjunctive Boolean queries. We provide an experimental evaluation of software implementation over an extensive real dataset containing millions of records. The results show that Nomos performance is comparable to the state-of-the-art static conjunctive SSE schemes in practice.

ePrint: https://eprint.iacr.org/2024/573

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