DETECTION OF PHISHING ATTACKS USING TLS TRAFFIC

Phishing attacks trick people into disclosing personal information like passwords and credit card numbers with the intention of stealing or corrupting sensitive data. Some of the existing phishing detection techniques like Content-Based, URL-Based, List-Based may not provide good security, because the attacker using the latest technologies to steal data. The Transport Layer is responsible for ensuring reliable and efficient data transfer between end systems (computers or devices) over a network. TLS is a cryptographic protocol used to secure communication over a computer network. In this work, TLS 1.2 and TLS 1.3 features will be used to train machine learning algorithms to increase the performance metrics. Phishing and Legitimate URLs are used to generate TLS features using the cyber security tools like Selenium and Wireshark. These TLS features will help to detect phishing URLs efficiently. This work includes machine learning algorithms like XGBOOST, Random Forest and Multi-Naïve Bayes will be used.