Advanced Phishing Content Identification Using Dynamic Weighting Integrated with Genetic Algorithm Optimization

Journal of Science Technology and Research (JSTAR) 5 (1):500-520 (2024)
  Copy   BIBTEX

Abstract

The Genetic Ranking Optimization Algorithm (GROA) is used to rank phishing content based on multiple features by optimizing the ranking system through iterative selection and weighting. Dynamic weighting further enhances the process by adjusting the weights of features based on their importance in real-time. This hybrid approach enables the model to learn from the data, improving classification over time. The classification system was evaluated using benchmark phishing datasets, and the results demonstrated a significant improvement in detection accuracy and reduced false positives.

Analytics

Added to PP
2024-10-08

Downloads
45 (#99,907)

6 months
45 (#94,823)

Historical graph of downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.
How can I increase my downloads?