Building ScamLens AI: My Exploration of Artificial Intelligence in Phishing and Social Engineering Detection

Title: Building ScamLens AI: Exploring Artificial Intelligence in Phishing and Social Engineering Detection

Zain Nofan Abuzaid, an Information Technology student and software developer from Jordan, has been exploring the application of artificial intelligence in cybersecurity, particularly in detecting phishing and social engineering attacks. His project, ScamLens AI, aims to analyze suspicious digital content and provide users with explanations as to why it is considered risky.

Connecting his research with development, ScamLens AI focuses on multiple indicators such as language analysis, URL analysis, and social engineering analysis. The system looks for techniques like urgency, fear, trust, impersonation, and manipulation to determine the likelihood of a message being malicious.

Explainability is a crucial aspect of ScamLens AI. While providing a risk score is useful, users need explanations for the results. For instance, a suspicious message may contain urgent requests, require sensitive information, or impersonate trusted organizations. By giving reasons behind the result, ScamLens AI becomes a more valuable decision support tool.

However, it is essential to understand that AI-based security tools are not infallible. They can produce false positives or false negatives and make mistakes when the available information is incomplete. Privacy is another significant concern, as users may share sensitive messages, emails, or screenshots for analysis. As such, ScamLens AI should be considered an AI-assisted security concept rather than a system that guarantees 100% accurate predictions.

In his future research, Abuzaid plans to explore machine learning-based phishing classification, natural language processing, and the analysis of screenshots and text together. He also plans to develop explainable AI for cybersecurity, human-centered security interfaces, and privacy-preserving analysis. These areas will further enhance the practical application of AI in detecting and preventing phishing and social engineering attacks.