Encryption algorithms based on block ciphers are among the most widely adopted solutions
for providing information security. Over the years, a variety of methods have been proposed …

Neural-aided cryptanalysis is a challenging topic, in which the neural distinguisher () is a
core module. In this paper, we propose a new considering multiple ciphertext pairs …

As IoT technology develops, many sensor devices are being used in our life. To protect such
sensor data, lightweight block cipher techniques such as SPECK-32 are applied. However …

Neural cryptanalysis is the study of cryptographic primitives throughmachine learning
techniques. Following Gohr's seminal paper at CRYPTO 2019, afocus has been placed on …

WARP is a 128-bit lightweight block cipher presented by S. Banik et al. at SAC 2020. It is
based on 32-nibble type-2 Generalised Feistel Network (GFN) structure and uses a …

Differential analysis is a vital tool for evaluating the security of cryptography algorithms.
There has been a growing interest in the differential distinguisher based on deep learning …

In this paper, we propose deep learning-based output prediction attacks in a blackbox
setting. As preliminary experiments, we first focus on two toy SPN block ciphers (small …

Machine Learning (ML) is almost ubiquitously used in multiple disciplines nowadays.
Recently, we have seen its usage in the realm of differential distinguishers for symmetric key …

Abstract At CRYPTO'19, A. Gohr proposed neural distinguishers for the lightweight block
cipher Speck32/64, achieving better results than the state-of-the-art at that point. However …

Differential cryptanalysis is one of the most critical analysis methods to evaluate the security
strength of cryptographic algorithms. This paper first applies the genetic algorithm to search …