Learning with Rounding: New Reduction, Properties and Applications

Provided by: IBM
Topic: Security
Format: PDF
The Learning With Rounding (LWR) problem, introduced by the researchers at EUROCRYPT '12, is a variant of Learning With Errors (LWE), where one replaces random errors with deterministic rounding. The LWR problem was shown to be as hard as LWE for a setting of parameters where the modulus and modulus-to-error ratio are super-polynomial. In this paper the authors resolve the main open problem of [BPR12] and give a new reduction that works for a larger range of parameters, allowing for a polynomial modulus and modulus-to-error ratio.

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