Machine learning methods for detection of phishing websites

In recent years, the rise in cybercrimes has significantly increased the vulnerability of the open internet to various threats and cyber-attacks. Among these, phishing stands out as one of the most perilous crimes worldwide. In a phishing attack, perpetrators create fraudulent websites that mimic legitimate ones (such as fake bank websites). These deceptive sites lure users into disclosing sensitive financial, personal, and confidential information. This project seeks to introduce machine learning and artificial intelligence techniques to effectively detect phishing websites. By leveraging these advanced methods, the goal is to enhance the ability to identify and mitigate the risks posed by fraudulent online platforms.