Title:	Machine-learning-aided side-channel analysis in post-quantum cryptography
DNr:	Berzelius-2024-53
Project Type:	LiU Berzelius
Principal Investigator:	Qian Guo <qian.guo@eit.lth.se>
Affiliation:	Lunds universitet
Duration:	2024-02-12 – 2024-09-01
Classification:	10201
Keywords:

Abstract

In the realm of cryptographic research, post-quantum cryptography has emerged as a central focus. The rapid strides in quantum computing technology have prompted the National Institute of Standards and Technology (NIST) to embark on a crucial mission: the Post-Quantum Cryptography Standardization Project. This initiative aims to identify robust replacements for our current public-key encryption and signature standards, which face imminent threats from quantum computers. As the project nears its conclusion, NIST is poised to unveil a new internet standard. Our research endeavors delve into the security of the selected cryptographic schemes, particularly when side-channel leakage is taken into account. The implications of our work extend far beyond theoretical realms; they directly impact the cryptographic techniques we rely on daily. As post-quantum cryptography becomes more widely deployed, our efforts contribute to securing sensitive information against potential cyberattacks from quantum computers