A Study of Distinguisher Attack on AES-128 and AES-256 Block Ciphers through Model Based Classification Using Neural Network

Abstract

Modern encryption algorithms will focus on transforming rendered text block into a non-rendered block of symbols. The objective is to make the cipher block more non-interpretable. Distinguisher attack algorithm is used to distinguish cipher text from random permutation and other related algorithms. Currently, a cipher has been design to concentrate on distinguisher attack. In this research work, we have attempted to distinguish the cipher blocks of AES-128 (Advanced Encryption Standard) and AES-256 symmetric block cipher algorithms using an artificial neural network based classifier.