<abstract xmlns="http://www.w3.org/1999/xhtml">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.</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.

Oblivious Lookup-Tables

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

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

Tatra Mountains Mathematical Publications

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Oblivious Lookup-Tables"}

Evaluating arbitrary functions on encrypted data is one of the holy grails of cryptography, with Fully Homomorphic Encryption (FHE) being probably the most...

Oblivious Lookup-Tables

Online veröffentlicht: 25. Feb. 2017

Seitenbereich: 191 - 203

Eingereicht: 02. Nov. 2015

DOI: https://doi.org/10.1515/tmmp-2016-0039

Schlüsselwörter
OLUT, homomorphic encryption, function evaluation

© 2016 Markus Stefan Wamser et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Oblivious Lookup-Tables

Online veröffentlicht: 25. Feb. 2017

Seitenbereich: 191 - 203

Eingereicht: 02. Nov. 2015

DOI: https://doi.org/10.1515/tmmp-2016-0039

SchlüsselwörterOLUT, homomorphic encryption, function evaluation

© 2016 Markus Stefan Wamser et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
OLUT, homomorphic encryption, function evaluation