Oblivious Lookup-Tables

Author:

Wamser Markus Stefan1,Rass Stefan2,Schartner Peter2

Affiliation:

1. Lehrstuhl für Sicherheit, in der Informationstechnik, Technische Universitäat München, Arcisstraße 21, D–80333 München, Germany

2. Institut für Angewandte Informatik, Alpen-Adria-Universität Klagenfurt, Universitätsstrasse 65-67, A–9020 Klagenfurt, Austria

Abstract

Abstract Evaluating arbitrary functions on encrypted data is one of the holy grails of cryptography, with Fully Homomorphic Encryption (FHE) being probably the most prominent and powerful example. FHE, in its current state is, however, not efficient enough for practical applications. On the other hand, simple homomorphic and somewhat homomorphic approaches are not powerful enough to support arbitrary computations. We propose a new approach towards a practicable system for evaluating functions on encrypted data. Our approach allows to chain an arbitrary number of computations, which makes it more powerful than existing efficient schemes. As with basic FHE we do not encrypt or in any way hide the function, that is evaluated on the encrypted data. It is, however, sufficient that the function description is known only to the evaluator. This situation arises in practice for software as a Software as a Service (SaaS)-scenarios, where an evaluator provides a function only known to him and the user wants to protect his data. Another application might be the analysis of sensitive data, such as medical records. In this paper we restrict ourselves to functions with only one input parameter, which allow arbitrary transformations on encrypted data.

Publisher

Walter de Gruyter GmbH

Subject

General Mathematics

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. False-Bottom Encryption: Deniable Encryption From Secret Sharing;IEEE Access;2023

2. The Mixture Graph-A Data Structure for Compressing, Rendering, and Querying Segmentation Histograms;IEEE Transactions on Visualization and Computer Graphics;2021-02

3. Homomorphic-Encrypted Volume Rendering;IEEE Transactions on Visualization and Computer Graphics;2021-02

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