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Communication Dans Un Congrès Année : 2021

SSE and SSD: Page-Efficient Searchable Symmetric Encryption

Résumé

Searchable Symmetric Encryption (SSE) enables a client to outsource a database to an untrusted server, while retaining the ability to securely search the data. The performance bottleneck of classic SSE schemes typically does not come from their fast, symmetric cryptographic operations, but rather from the cost of memory accesses. To address this issue, many works in the literature have considered the notion of locality, a simple design criterion that helps capture the cost of memory accesses in traditional storage media, such as Hard Disk Drives. A common thread among many SSE schemes aiming to improve locality is that they are built on top of new memory allocation schemes, which form the technical core of the constructions. The starting observation of this work is that for newer storage media such as Solid State Drives (SSDs), which have become increasingly common, locality is not a good predictor of practical performance. Instead, SSD performance mainly depends on page efficiency, that is, reading as few pages as possible. We define this notion, and identify a simple memory allocation problem, Data-Independent Packing (DIP), that captures the main technical challenge required to build page-efficient SSE. As our main result, we build a page-efficient and storage-efficient data-independent packing scheme, and deduce the Tethys SSE scheme, the first SSE scheme to achieve at once O(1) page efficiency and O(1) storage efficiency. The technical core of the result is a new generalization of cuckoo hashing to items of variable size. Practical experiments show that this new approach achieves excellent performance.
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Dates et versions

hal-03377462 , version 1 (14-10-2021)

Identifiants

  • HAL Id : hal-03377462 , version 1

Citer

Angèle Bossuat, Raphael Bost, Pierre-Alain Fouque, Brice Minaud, Michael Reichle. SSE and SSD: Page-Efficient Searchable Symmetric Encryption. Crypto 2021 - Annual International Cryptology Conference, Aug 2021, Virtual, France. ⟨hal-03377462⟩
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