AI-Driven Next-Generation Firewall for Dynamic Threat Detection and Zero Trust Implementation

Abstract

The increasing adoption of cloud computing, remote work environments, Internet of Things (IoT) devices, and encrypted communication has significantly expanded the attack surface of modern enterprise networks. Traditional rule-based and signature-driven firewall systems are no longer sufficient to defend against advanced cyber threats such as zero-day attacks, lateral movement, and stealthy intrusion attempts. These conventional approaches lack adaptability, generate high false-positive rates, and fail to provide continuous trust evaluation required in dynamic network environments.
To address these limitations, this paper proposes an AI-driven Next-generation firewall (NGFW) architecture designed to support dynamic threat detection and Zero Trust implementation. The proposed framework integrates network traffic monitoring, behavioral flow analysis, AI-based threat detection, and dynamic policy enforcement into a unified security system. By analyzing traffic patterns at the flow level, the system continuously evaluates risk and enforces least-privilege access decisions without relying on static rules or predefined signatures.