Efficient Cybersecurity Assessment Using SVM and Fuzzy Evidential Reasoning for Resilient Infrastructure
Journal:
arXiv
Published Date:
Jun 28, 2025
Abstract
With current advancement in hybermedia knowledges, the privacy of digital
information has developed a critical problem. To overawed the susceptibilities
of present security protocols, scholars tend to focus mainly on efforts on
alternation of current protocols. Over past decade, various proposed encoding
models have been shown insecurity, leading to main threats against significant
data. Utilizing the suitable encryption model is very vital means of guard
against various such, but algorithm is selected based on the dependency of data
which need to be secured. Moreover, testing potentiality of the security
assessment one by one to identify the best choice can take a vital time for
processing. For faster and precisive identification of assessment algorithm, we
suggest a security phase exposure model for cipher encryption technique by
invoking Support Vector Machine (SVM). In this work, we form a dataset using
usual security components like contrast, homogeneity. To overcome the
uncertainty in analysing the security and lack of ability of processing data to
a risk assessment mechanism. To overcome with such complications, this paper
proposes an assessment model for security issues using fuzzy evidential
reasoning (ER) approaches. Significantly, the model can be utilised to process
and assemble risk assessment data on various aspects in systematic ways. To
estimate the performance of our framework, we have various analyses like,
recall, F1 score and accuracy.
