Oblivious Lookup-Tables

Open access

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.

List of acronymsDEG:

Damgård’s ElGamal

ECC:

Elliptic Curve Cryptography

FHE:

Fully Homomorphic Encryption

MPC:

Multiparty Computation

OLUT:

Oblivious Lookup Table

OT:

Oblivious Transfer

PIR:

Private Information Retrieval

SaaS:

Software as a Service

UAC:

Universal Arithmetic Circuit

REFERENCES

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Tatra Mountains Mathematical Publications

The Journal of Slovak Academy of Sciences

Journal Information


Cite Score 2016: 0.32

SCImago Journal Rank (SJR) 2016: 0.309
Source Normalized Impact per Paper (SNIP) 2016: 0.500

Mathematical Citation Quotient (MCQ) 2016: 0.11

Target Group

researchers in the all fields of mathematical research

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