<![CDATA[The increasing complexity of modern computer networks requires network management systems that are more automated, flexible, secure, and adaptive. Intent-Based Networking (IBN) has emerged as a network management approach that enables user requirements to be translated into automated network configurations based on high-level intents. This study aims to analyze research developments related to security and automation in Intent-Based Networking using the Systematic Literature Review (SLR) method. The research methodology follows the PRISMA 2020 framework to ensure a systematic and transparent literature selection process. Relevant studies were collected from several international scientific databases, including IEEE Xplore, ScienceDirect, SpringerLink, Google Scholar, and ACM Digital Library during the 2021–2026 period. The results show that IBN implementation improves network management efficiency through automated configuration, real-time network monitoring, and network service optimization based on Artificial Intelligence (AI). The integration of Software Defined Networking (SDN), Machine Learning, and security orchestration also supports the development of more adaptive and intelligent networks. However, IBN implementation still faces several challenges, such as intent manipulation, policy translation errors, increased attack surface, and the complexity of integrating network automation systems. This study provides a comprehensive synthesis of security and automation developments in Intent-Based Networking and can serve as a reference for developing more secure, flexible, and adaptive automated networks in the future.]]>
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