NEXT-GENERATION FIREWALLS: ARCHITECTURE AND EFFECTIVENESS
Abstract
IT is developing at an astonishing rate, which has significantly altered the distributed network's perimeter. Therefore, the conventional ideas of security are insufficient. Port-based firewalls are now essentially worthless since smart cyber threats are emerging to take advantage of the weaknesses in traditional security tools as more and more companies use analytics, cloud computing, and other automation tools to accelerate the development of new goods and services to satisfy consumer demand. Advanced firewalls such as Web Applications firewalls (WAFWs) and next generation firewalls (NGFWs) have been developed to address these issues. With an emphasis on extra features like DPI, application filtering, and AI implementation, this article aims to explain how NGFWs evolved and integrated with cloud solutions. Accordingly, this study evaluates the effectiveness of AI-based firewalls in fending off contemporary cyberthreats by utilizing advanced techniques such as machine learning and deep learning. The study looks at AI-based firewalls' ability to provide consistent performance in dynamic networks and focuses on how well they work in the cloud. This study illustrates the real performance of various AI-based firewall architectures, including their capacity to identify threats, false positives, and time consumption, without any theoretical simulation. Along with discussing potential disadvantages and potential changes, the article also examines the problems associated with using these advanced firewalls in cloud systems. In order to defend the current complex enterprise environments, including the usage of cloud services, this research provides a literature evaluation of the NGFWs and WAFWs and their relevance. The results broaden our understanding of cyber security management and point to AI's potential as a crucial facilitator of resource management, growth, and detection in the context of cloud security.
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