Next-generation network security: conceptualizing a Unified, AI-Powered Security Architecture for Cloud-Native and On-Premise Environments

Sunday Adeola Oladosu 1, *, Adebimpe Bolatito Ige 2, Christian Chukwuemeka Ike 3, Peter Adeyemo Adepoju 4, Olukunle Oladipupo Amoo 5 and Adeoye Idowu Afolabi 6

1 Independent Researcher, Texas, USA.
2 Independent Researcher, Canada.
3 Globacom Nigeria Limited.
4 Independent Researcher, Lagos, Nigeria.
5 Amstek Nigeria Limited.
6 CISCO, Nigeria.
 
Review
International Journal of Science and Technology Research Archive, 2022, 03(02), 270–280.
Article DOI: 10.53771/ijstra.2022.3.2.0143
Publication history: 
Received on 27 October 2022; revised on 08 December 2022; accepted on 11 December 2022
 
Abstract: 
The increasing complexity and interconnectivity of modern IT infrastructures, including both cloud-native and on-premise environments, present significant challenges for traditional network security models. As organizations adopt hybrid cloud architectures and expand their reliance on cloud-native technologies, ensuring robust security across diverse environments becomes essential. This review proposes a conceptual framework for next-generation network security, centered around a unified, AI-powered architecture that seamlessly integrates cloud-native and on-premise systems. By leveraging artificial intelligence (AI) and machine learning (ML), the framework aims to enhance threat detection, response automation, and overall network security. The proposed AI-powered security architecture provides real-time monitoring, predictive threat analysis, and automated incident response, enabling organizations to proactively address emerging threats across hybrid environments. AI-driven analytics can detect anomalies, identify vulnerabilities, and prioritize risks with unprecedented accuracy, allowing for swift mitigation actions before potential breaches escalate. The architecture also integrates Zero Trust principles, ensuring that every access request is continuously verified, regardless of its origin, to protect sensitive resources. Additionally, the framework emphasizes the importance of cross-platform interoperability, enabling centralized management of security policies and incidents, regardless of whether data resides in on-premise systems or cloud infrastructures. By implementing a unified security model, organizations can simplify their security operations, reduce overhead, and improve the consistency of policy enforcement across environments. The review concludes by examining the potential impact of this unified AI-powered security framework on industries such as finance, healthcare, and e-commerce, where data protection and regulatory compliance are critical. As cyber threats become increasingly sophisticated, this conceptual architecture represents a proactive, scalable solution to safeguard organizational networks in the evolving digital landscape.

 

Keywords: 
Network security; AI-powered security; Cloud-native; On-premise environments
 
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