Fuzzification-based Feature Selection for Enhanced Website Content Encryption

Mike Wa Nkongolo

Paper 2023/987

Fuzzification-based Feature Selection for Enhanced Website Content Encryption

Mike Wa Nkongolo

, University of Pretoria

Abstract

We propose a novel approach that utilizes fuzzification theory to perform feature selection on website content for encryption purposes. Our objective is to identify and select the most relevant features from the website by harnessing the principles of fuzzy logic. Fuzzification allows us to transform the crisp website content into fuzzy representations, enabling a more nuanced analysis of their characteristics. By considering the degree of membership of each feature in different fuzzy categories, we can evaluate their importance and relevance for encryption. This approach enables us to prioritize and focus on the features that exhibit higher membership degrees, indicating their significance in the encryption process. By employing fuzzification-based feature selection, we aim to enhance the effectiveness and efficiency of website content encryption, ultimately improving the overall internet security

Metadata

Available format(s): PDF
Category: Cryptographic protocols
Publication info: Preprint.
Keywords: Fuzzy logic encryption information retrieval
Contact author(s): mike wankongolo @ up ac za
History: 2023-06-26: approved; 2023-06-24: received; See all versions
Short URL: https://ia.cr/2023/987
License: CC BY

BibTeX

@misc{cryptoeprint:2023/987,
      author = {Mike Wa Nkongolo},
      title = {Fuzzification-based Feature Selection for Enhanced Website Content Encryption},
      howpublished = {Cryptology {ePrint} Archive, Paper 2023/987},
      year = {2023},
      url = {https://eprint.iacr.org/2023/987}
}