Fuzzy Feature Selection with Key-based Cryptographic Transformations
Mike Nkongolo
In the field of cryptography, the selection of relevant features plays a
crucial role in enhancing the security and efficiency of cryptographic
algorithms. This paper presents a novel approach of applying fuzzy feature
selection to key-based cryptographic transformations. The proposed fuzzy
feature selection leverages the power of fuzzy logic to identify and select
optimal subsets of features that contribute most effectively to the
cryptographic transformation process. By incorporating fuzzy feature selection
into key-based cryptographic transformations, this research aims to improve the
resistance against attacks and enhance the overall performance of cryptographic
systems. Experimental evaluations may demonstrate the effectiveness of the
proposed approach in selecting secure key features with minimal computational
overhead. This paper highlights the potential of fuzzy feature selection as a
valuable tool in the design and optimization of key-based cryptographic
algorithms, contributing to the advancement of secure information exchange and
communication in various domains.