Abstract At CRYPTO 2019, A. Gohr introduced Neural Differential Cryptanalysis by applying
deep learning to modern block cipher cryptanalysis. Surprisingly, the resulting neural …

Masked cryptographic implementations can be vulnerable to higher-order attacks. For
instance, deep neural networks have proven effective for second-order profiling side …

Deep neural networks (DNNs) represent a powerful technique for assessing cryptographic
security concerning side-channel analysis (SCA) due to their ability to aggregate leakages …

Side-channel attacks leverage correlations between power consumption and intermediate
encryption results to infer encryption keys. Recent studies show that deep learning offers …

As cryptographic implementations leak secret information through side-channel emissions,
the Hamming weight (HW) leakage model is widely used in deep learning profiling side …

Abstract Schemes such as Common Criteria or FIPS 140-3 require the assessment of
cryptographic implementations with respect to side channels at high security levels. Instead …

Recently, deep learning-based side-channel analysis (DLSCA) has emerged as a serious
threat against cryptographic implementations. These methods can efficiently break …

In the surge of the digital era, the metaverse, as a groundbreaking concept, has become a
focal point in the technology sector. It is reshaping human work and life patterns, carving out …

The use of deep learning-based side-channel analysis is an effective way of performing
profiling attacks on power and electromagnetic leakages, even against targets protected …

In recent years, side-channel analysis based on deep learning has garnered significant
attention from researchers. A pivotal reason for this lies in the fact that deep learning-based …