Abstract
Public-key cryptographic schemes currently in use depend on the intractability of certain mathematical problems such as integer factorization or the discrete logarithm. However, Shor’s algorithm can solve these problems in polynomial time if large-scale quantum computers become available. This will compromise the security of today’s public-key cryptosystems. To address this issue, new public-key cryptographic primitives are being developed. One of them is Saber whose security relies on the Learning With Rounding (LWR) problem that is believed to be hard for quantum computers. The resistance of unprotected and first-order masked implementations of Saber to side-channel attacks has been already investigated. In this paper, we demonstrate the first successful message and secret key recovery attacks on the second- and third-order masked implementations of Saber in ARM Cortex-M4 CPU by deep learning-based power analysis. Our experimental results show that currently available software implementations of Saber need better protection.
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