Generative AI in Cybersecurity: A Systematic and Netnographic Review of Opportunities, Threats, and Challenges

Abstract

This research examines the opportunities, threats, and challenges of applying Generative AI (GenAI) in cybersecurity through a comprehensive Systematic Literature Review (SLR) and Netnography. This study expands the existing literature by analyzing how GenAI can facilitate the creation of AI-driven defenses against AI-generated threats, augment human-AI collaboration in security operations, advocate for the ethical and transparent use of AI, and enhance access to sophisticated tools for smaller organizations. The findings underscore GenAI’s dual influence, providing robust capabilities for threat identification and automation but simultaneously facilitating more advanced cyberattacks and eliciting concerns over bias, supervision, and skill erosion. This study enhances the understanding of GenAI’s transformative impact on cybersecurity practices by integrating academic research with real-time community feedback, while also outlining the practical and ethical implications of its adoption. The study provides timely insight into leveraging GenAI’s potential while mitigating its risks, thus significantly advancing cybersecurity and AI governance research.