As cyber threats continue to evolve in both sophistication and scale, traditional network security approaches are no longer sufficient to safeguard enterprise infrastructures. The emergence of advanced technologies such as Artificial Intelligence (AI), Zero Trust frameworks, and cloud-native solutions offers promising pathways for next-generation network security. This article explores how these technologies can be leveraged to enhance threat detection, prevention, and response in dynamic and distributed environments. First, it examines the role of AI in automating threat identification through machine learning and anomaly detection, providing a proactive approach to network defense. The paper then delves into the Zero Trust security model, emphasizing its core principle of "never trust, always verify," which minimizes the risk of unauthorized access within the network perimeter. Additionally, the article explores how cloud-native security solutions are reshaping network architectures, enabling scalable and agile defense mechanisms that adapt to the complexities of hybrid and multi-cloud environments. By integrating these cutting-edge technologies, organizations can better address the modern landscape of cyber threats, including insider attacks, data breaches, and sophisticated malware. The article concludes by highlighting best practices for implementing AI-driven, Zero Trust, and cloud-native security strategies to build resilient, adaptive networks that remain secure amid evolving cyber challenges.
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