A survey on phishing website detection in Machine learning and Neural networks

This literature survey examines software-based phishing detection techniques, a critical area of cybersecurity. With phishing attacks growing rapidly each year, this study explores the phishing ecosystem, current statistics, automatic detection schemes, feature analysis, datasets, algorithms, and evaluation metrics. Emphasis is given to the challenges in feature robustness, handling adaptive attacks, and limitations in large-scale data processing. The survey also identifies research gaps in addressing new attack vectors, offering insights for future directions.