Keywords
machine learning
network security
deep learning
Abstract
The integration of artificial intelligence (AI) into computer networks has rapidly evolved, influencing network architecture, security measures, and traffic management. This paper explores AI's transformative impact on these areas, focusing on advancements in machine learning (ML), deep learning (DL), and reinforcement learning. These innovations are reshaping network security by improving threat detection and anomaly identification, as well as enhancing traffic management through predictive and adaptive routing. AI-driven systems are also making strides in automating network management tasks, allowing for more efficient resource allocation and self-healing networks. Despite these advancements, challenges remain, particularly concerning the integration of AI with legacy infrastructures and the ethical implications of AI decision-making processes.
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