Preventive Measures for Network Security Using Generative Artificial Intelligence

Abstract

With the rapid expansion of digital infrastructure, network security has become a critical concern for organizations and individuals alike. Cyber threats such as phishing, malware, Distributed Denial of Service (DDoS) attacks, and insider threats continue to evolve, demanding advanced preventive mechanisms. Generative Artificial Intelligence (GAI) has emerged as a powerful tool to proactively safeguard networks by detecting vulnerabilities, generating synthetic data for threat analysis, and automating security responses. This paper explores the role of GAI in enhancing network security through anomaly detection, adversarial training, and automated security patch generation. Additionally, it examines the challenges, ethical concerns, and future trends in leveraging GAI for cybersecurity.

Keywords: Network Security, Generative Artificial Intelligence, Cyber Threats, Anomaly Detection, Adversarial Training, Automated Security