AI-Driven Phishing Attack and Threat Detection and Mitigation

The article examines the emergence of AI-based phishing attacks, their detection, and prevention measures. Due to the development of phishing methods along with the development of AI, old ways of detecting them cannot keep pace, so it is highly important to move to more advanced methods. The paper will look at the use of AI in detecting phishing attacks using machine learning, natural language processing, and anomaly detectors. The main results show the usefulness of AI in detecting threats in real-time, minimizing inaccurate alarms, and automated response to mitigation. The paper also addresses several AI-based phishing detection systems, including the Gmail defense developed by Google and the threat intelligence platform provided by PhishLabs, presenting the practical use of the systems. In addition, the article reviews the shortcomings and drawbacks of deploying AI-based systems such as data quality concerns and model reconfigurability. The results indicate that even though AI presents significant advantages in the fight against phishing, further study and development are further needed to make the system more accurate and scalable in the constantly changing cybersecurity environment.