  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.
