Single-Trace Attack on NIST Round 3 Candidate Dilithium Using Machine Learning-Based Profiling
Jaeseung Han, Tae-Ho Lee, Jihoon Kwon, Joohee Lee, Il-Ju Kim, Jihoon Cho, Dong‐Guk Han, Bo-Yeon Sim · IEEE Access · 2021
In this paper, we propose single-trace side-channel attacks against CRYSTALS-DILITHIUM. CRYSTALS-DILITHIUM is a lattice-based digital signature algorithm, one of the third round finalists of the national institute of standards and technology (NIST) standardization project. We attack number-theoretic transform (NTT) in the signing procedure and key generation of CRYSTALS-DILITHIUM to obtain a secret key. When targeting the signing procedure, we can recover both secret key vectors s1 and s2. This enables forgery of signatures. However, only the secret key vector s1 can be recovered when targeting the key generation. Thus, we additionally attack four operations, sampling, addition, rounding, and packing, to find s2. We applied a machine learning-based profiling attack method to find the secret key vectors s1 and s2 with a single trace.