Phishing Site Detection using Machine Learning

Phishing web sites are a big cybersecurity threat, frequently serving as access factors for assaults that compromise facts confidentiality and integrity. This studies proposes a gadget getting to know-primarily based totally method to discover phishing webweb sites via way of means of extracting and reading capabilities from URLs and internet site content. By leveraging algorithms inclusive of choice bushes and deep neural networks, this version is skilled to become aware of phishing styles on categorized datasets. To deal with facts imbalance and beautify version performance, oversampling and ensemble getting to know strategies are applied. Explainable AI techniques enhance interpretability, presenting insights into detection processes. The version is evaluated the use of real-international datasets, displaying better accuracy and robustness in comparison to present techniques. This method holds promise for advancing phishing detection, important for countering cyber threats and improving on line security. Continued studies is vital to live in advance of evolving phishing tactics.