Abstract
We study encrypted storage schemes where a client outsources data to an untrusted third-party server (such as a cloud storage provider) while maintaining the ability to privately query and dynamically update the data. We focus on encrypted multi-maps (EMMs), a structured encryption (STE) scheme that stores pairs of label and value tuples. EMMs allow queries on labels and return the associated value tuple. As responses are variable-length, EMMs are subject to volume leakage attacks introduced by Kellaris et al. [CCS'16]. To prevent these attacks, volume-hiding EMMs were introduced by Kamara and Moataz [Eurocrypt'19] that hide the label volumes (i.e., the value tuple lengths). As our main contribution, we present the first fully dynamic volume-hiding EMMs that are both asymptotically and concretely efficient. Furthermore, they are simultaneously forward and backward private which are the de-facto standard security notions for dynamic STE schemes. Additionally, we implement our schemes to showcase their concrete efficiency. Our experimental evaluations show that our constructions are able to add dynamicity with minimal to no additional cost compared to the prior best static volume-hiding schemes of Patel et al. [CCS'19].
Publisher
Privacy Enhancing Technologies Symposium Advisory Board
Cited by
8 articles.
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1. Tutorial: Information Leakage from Cryptographic Techniques;2024 IEEE 44th International Conference on Distributed Computing Systems Workshops (ICDCSW);2024-07-23
2. Exploiting Update Leakage in Searchable Symmetric Encryption;Proceedings of the Fourteenth ACM Conference on Data and Application Security and Privacy;2024-06-19
3. Encrypted Multi-map that Hides Query, Access, and Volume Patterns;Lecture Notes in Computer Science;2024
4. Leakage-Abuse Attacks Against Forward and Backward Private Searchable Symmetric Encryption;Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security;2023-11-15
5. Conjunctive Searchable Symmetric Encryption from Hard Lattices;2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P);2023-07