AI-Powered Phishing Detection and Mid Stalker Analyzer

With the increasing dependence on digital platforms for communication, financial transactions, and social interactions, cybersecurity threats have grown significantly in recent years. Among these threats, phishing attacks and online stalking have emerged as major concerns due to theirability to exploit user behavior and compromise sensitive information. Phishing attacks deceive users into revealing confidential data through fake websites,emails, or messages, while stalker activities involve monitoring and analyzing user interactions formalicious purposes. Traditional cybersecurity solutions rely on static rule based mechanisms, which are often ineffective againstmodern, evolving attack techniques. These systems fail to adapt to dynamic patterns and lack real-timedetection  capabilities, vulnerability for users.resulting  inincreased This research proposes an intelligent system that integrates phishing detection and mid-stalker analysisusing artificial intelligence techniques. The system  utilizes machine learning algorithms, natural language processing, and behavioral pattern analysis to identify malicious URLs, detect suspicious email content, and monitor abnormal user activity. By combining contentbased and behavior-based detection, the system provides a comprehensive security solution. INDEX TERMS: Phishing Detection, Cybersecurity, Machine Learning, NLP, Behavioral Analysis,Anomaly Detection, AI Security