Applying Large Language Model (LLM) for Developing Cybersecurity Policies to Counteract Spear Phishing Attacks on Senior Corporate Managers

Abstract

Applying Google Gemini's generative AI capabilities, this research provided a novel approach to developing and implementing cybersecurity policies targeted at mitigating spear phishing attacks against senior corporate managers. The study demonstrated significant enhancements in the detection, prevention, and response strategies within corporate cybersecurity frameworks, by integrating advanced artificial intelligence with traditional security protocols. The application of machine learning algorithms not only improved the accuracy and speed of threat detection but also enabled dynamic policy adjustments based on real-time data analysis, proving crucial in the evolving landscape of digital threats. The findings underscore the potential of AI to transform cybersecurity practices, offering more adaptable, proactive, and robust defenses against increasingly sophisticated spear phishing techniques. Further, the study explores the implications of AI-driven policies for corporate governance and compliance, suggesting a new paradigm in which AI not only supports but actively defines strategic security decisions. The promising results invite further investigation into broader applications of AI in cybersecurity, pointing toward a future where AI integration is standard in the defense against complex cyber threats.