Comparative Analysis of Machine Learning Algorithms for Phishing Website Detection Using Random Forest

Key Points

• Phishing website detection accuracy improved significantly with random forest algorithm, displaying superior performance over other machine learning methods.
• Key evidence shows that random forest achieved a 95% accuracy rate in identifying phishing sites, based on a comprehensive dataset.
• A comparative analysis of various machine learning algorithms was conducted to determine their efficacy in phishing detection.
• These findings underscore the importance of algorithm selection in enhancing cybersecurity measures against phishing attacks.