AI/ML for cybersecurity and robustness in optical networks: Key opportunities and challenges
The rapid evolution of optical networks has introduced new challenges in cybersecurity and network robustness, necessitating innovative solutions to ensure reliable and secure communication. This paper explores the opportunities and challenges of applying Artificial Intelligence (AI) and Machine Lea...
| Autores: | , , , , , , |
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| Formato: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2025 |
| País: | España |
| Recursos: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10256/27200 |
| Acesso em linha: | http://hdl.handle.net/10256/27200 |
| Access Level: | acceso embargado |
| Palavra-chave: | Seguretat informática -- Congressos Computer security -- Congresses |
| Resumo: | The rapid evolution of optical networks has introduced new challenges in cybersecurity and network robustness, necessitating innovative solutions to ensure reliable and secure communication. This paper explores the opportunities and challenges of applying Artificial Intelligence (AI) and Machine Learning (ML) techniques to enhance the security and resilience of optical networks. We present a comprehensive survey of current AI/ML applications in optical networks, focusing on anomaly detection, threat mitigation, and adaptive resource management. By highlighting current limitations and proposing future research directions, this paper aims to provide a roadmap for enhancing AI/ML-driven methods to build secure, robust, and efficient optical networks |
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