Novel Scheme for Robust Confusion Component Selection Based on Pythagorean Fuzzy Set

Abstract

The substitution box, often known as an S-box, is a nonlinear component that is a part of several block ciphers. Its purpose is to protect cryptographic algorithms from a variety of cryptanalytic assaults. A MultiCriteria Decision Making (MCDM) problem has a complex selection procedure because of having many options and criteria to choose from. Because of this, statistical methods are necessary to assess the performance score of each S-box and decide which option is the best one available based on this score. Using the Pythagorean Fuzzy-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, the major objective of this investigation is to select the optimal S-box to be implemented from a pool of twelve key choices. With the help of the Pythagorean fuzzy set (PFS), the purpose of this article is to evaluate whether this nonlinear component is suitable for use in a variety of encryption applications. In this article, we have considered various characteristics of S-boxes, including nonlinearity, algebraic degree, strict avalanche criterion (SAC), absolute indicator, bit independent criterion (BIC), sum of square indicator, algebraic immunity, transparency order, robustness to differential cryptanalysis, composite algebraic immunity, signal to noise ratio-differential power attack (SNR-DPA), and confusion coefficient variance on some standard S-boxes that are Advanced Encryption Following this, the findings of the investigation are changed into Pythagorean fuzzy numbers in the shape of a matrix. This matrix is then subjected to an analysis using the TOPSIS method, which is dependent on the Pythagorean fuzzy set, to rank the most suitable S-box for use in encryption applications.