Implementation of Generative AI in Enhancing Cyber Threat Intelligence and Next Generation Firewalls
Sumit Kumar Das, Payal Panda · International Journal for Research in Applied Science and Engineering Technology · 2025
Abstract: Cybersecurity is a critical concern in the digital age, demanding advanced and innovative approaches to safeguard sensitive information and systems. This research conducts a strong examination of next-generation firewalls (NGFWs) that can be integrated with artificial intelligence (AI). As traditional firewalls fall short in addressing modern cyber threats, the incorporation of AI provides a promising avenue for enhanced threat detection and mitigation. Leveraging machine learning and deep learning approaches, the study assesses key performance metrics such as detection accuracy, false positive rates, and computational efficiency. The goal is to provide a clear understanding of the strengths and weaknesses inherent in each approach, facilitating an informed evaluation. The comparative analysis section which includes graphical representations to throw light on the findings, offering a visual overview of the performance disparities among selected AI-based firewall methods. Pros and cons are meticulously examined, providing everyone with valuable insights for decision-making in cybersecurity strategy. This research aims to contribute to the ongoing discourse on AI-based firewalls, addressing current limitations and paving the way for advancements that fortify the cybersecurity landscape