Application of Machine Learning in DES Cryptanalysis

Web proceedings papers

Authors

Stefan Andonov , Jovana Dobreva , Lina Lumburovska , Stefan Pavlov , Vesna Dimitrova and Aleksandra Popovska-Mitrovikj

Abstract

The usage of machine learning is expanding over all scientific fields and this branch is becoming more and more popular in the last years. In this paper we consider application of machine learning in the cryptanalysis, precisely in cryptanalysis of DES algorithm. This algorithm works in 16 rounds and we make two analyses: one for only one round and one for all rounds. We use different datasets and specific neural network for each analysis. We present results from several experiments for different datasets and different keys. Furthermore, we analyze and compare the obtained results, where we provide visual and textual presentation and we derive some conclusions.

Keywords

Machine learning, DES, Cryptanalysis, Neural networks, Datasets