The impact of intent-based networking on network configuration management and security
1 J. Warren McClure School of Emerging Communication Technologies, Ohio University, Athens, Ohio, USA.
2 Department of Computer Science, New Mexico Highlands University Las Vegas, New Mexico, USA.
3 Information Technology Department, Softbrooks, Sheridan, Wyoming, USA.
Review Article
Global Journal of Engineering and Technology Advances, 2025, 22(01), 063-068.
Article DOI: 10.30574/gjeta.2025.22.1.0012
Publication history:
Received on 03 December 2024; revised on 12 January 2025; accepted on 14 January 2025
Abstract:
Intent-based networking (IBN) has emerged as a transformative paradigm in network management, revolutionizing how networks are configured, monitored, and secured. By leveraging artificial intelligence (AI) and machine learning (ML), IBN translates high-level business objectives into automated network configurations, ensuring that operational intents are consistently achieved. This paper explores the profound impact of IBN on network configuration management and security.
Firstly, we examine how IBN streamlines network configuration through automation, reducing manual intervention and mitigating configuration errors, which are among the leading causes of network outages. IBN’s ability to validate intents against real-time network states ensures that configurations align with business policies, enabling agile and reliable network operations.
Secondly, the role of IBN in enhancing network security is analyzed. By continuously monitoring network behavior against predefined intents, IBN systems can detect and respond to anomalies or potential threats in real time. This proactive approach minimizes the window of vulnerability and ensures compliance with security policies. Furthermore, the use of AI-driven insights facilitates predictive threat management and adaptive security measures.
Finally, we discuss the challenges and future prospects of adopting IBN, including the integration with legacy systems, the reliance on accurate intent definitions, and the need for robust AI models. The findings underscore that IBN not only simplifies network management but also fortifies network defenses, making it a cornerstone of modern, resilient network architectures.
Keywords:
Intent-Based Networking (IBN); Network Configuration Management (NCM); Artificial Intelligence (AI); Machine Learning (ML)
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Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0