Innovative Data Transposition in HCS using Genetic Algorithm Feature Selection

Data protection is improving now in cryptography; one such safe cryptographic method is the honey cypher structure. While there are other security structures available, the Honey Cypher structure is a recent approach that offers protection for both numeric and alphabetic plaintext. We intended to put this eight-level structure into practice. The first level has eight elements; one element decreases from the first level to the last level; and the last level has just one element. The password fills the first level of this honey cypher structure; repeated letters are removed, and the password may contain numbers. The data transformation is required to give a better solution, which is possible by using genetic algorithmic operations. The structure of honey is made of all letters and numbers; the honey form is transformed into the honey cypher structure. The structure made up of these values is referred to as the fitness values. Convert these values into binary form; this form is fragmented into offsets. The mutation function is applied to two pairs of offsets in order to produce two distinct pairs of new generations. This new generation is considered a pair of cipher texts. This cipher text is transformed into a recipient, and the receiver retrieves the original message by applying the genetic algorithm mutation function.