TY - JOUR AU - Robyns, Pieter AU - Quax, Peter AU - Lamotte, Wim PY - 2018/11/09 Y2 - 2024/03/29 TI - Improving CEMA using Correlation Optimization JF - IACR Transactions on Cryptographic Hardware and Embedded Systems JA - TCHES VL - 2019 IS - 1 SE - Articles DO - 10.13154/tches.v2019.i1.1-24 UR - https://tches.iacr.org/index.php/TCHES/article/view/7332 SP - 1-24 AB - <p>Sensitive cryptographic information, e.g. AES secret keys, can be extracted from the electromagnetic (EM) leakages unintentionally emitted by a device using techniques such as Correlation Electromagnetic Analysis (CEMA). In this paper, we introduce Correlation Optimization (CO), a novel approach that improves CEMA attacks by formulating the selection of useful EM leakage samples in a trace as a machine learning optimization problem. To this end, we propose the correlation loss function, which aims to maximize the Pearson correlation between a set of EM traces and the true AES key during training. We show that CO works with high-dimensional and noisy traces, regardless of time-domain trace alignment and without requiring prior knowledge of the power consumption characteristics of the cryptographic hardware. We evaluate our approach using the ASCAD benchmark dataset and a custom dataset of EM leakages from an Arduino Duemilanove, captured with a USRP B200 SDR. Our results indicate that the masked AES implementation used in all three ASCAD datasets can be broken with a shallow Multilayer Perceptron model, whilst requiring only 1,000 test traces on average. A similar methodology was employed to break the unprotected AES implementation from our custom dataset, using 22,000 unaligned and unfiltered test traces.</p> ER -