IACR News item: 31 March 2023
Debranjan Pal, Upasana Mandal, Abhijit Das, Dipanwita Roy Chowdhury
Deep learning-based cryptanalysis is one of the emerging
trends in recent times. Differential cryptanalysis is one of the most po-
tent approaches to classical cryptanalysis. Researchers are now modeling
classical differential cryptanalysis by applying deep learning-based tech-
niques. In this paper, we report deep learning-based differential distin-
guishers for block cipher PRIDE and RC5, utilizing deep learning models:
CNN, LGBM and LSTM. We found distinguishers up to 23 rounds for
PRIDE and nine rounds for RC5. To the best of our knowledge this is
the first deep learning based differential classifier for cipher PRIDE and
RC5.
Additional news items may be found on the IACR news page.