In recent years, the network paradigms of Software Defined Networking and Network Function Virtualization have gained significant traction, leading to the emergence of new network architectures that emphasize flexibility and adaptability. However, the rapid evolution of these paradigms has outpaced the development of effective cybersecurity management solutions, which remain largely reliant on traditional, manual processes. In this context, my doctoral research aims to advance network security automation by integrating Artificial Intelligence and formal methods into hybrid approaches for automating the configuration of network security functions. These approaches seek to combine the strengths of both fields,which are formal correctness, optimization, and computational efficiency. In this paper, I present the research questions and directions that will guide my PhD activity in developing such hybrid approaches.

Adaptive, Agile and Automated Cybersecurity Management / Bachiorrini, Gianmarco; Bringhenti, Daniele; Valenza, Fulvio. - ELETTRONICO. - (2025), pp. 273-276. (Intervento presentato al convegno 2025 IEEE 11th International Conference on Network Softwarization (NetSoft) tenutosi a Budapest (HU) nel 23-27 June 2025) [10.1109/NetSoft64993.2025.11080611].

Adaptive, Agile and Automated Cybersecurity Management

Gianmarco Bachiorrini;Daniele Bringhenti;Fulvio Valenza
2025

Abstract

In recent years, the network paradigms of Software Defined Networking and Network Function Virtualization have gained significant traction, leading to the emergence of new network architectures that emphasize flexibility and adaptability. However, the rapid evolution of these paradigms has outpaced the development of effective cybersecurity management solutions, which remain largely reliant on traditional, manual processes. In this context, my doctoral research aims to advance network security automation by integrating Artificial Intelligence and formal methods into hybrid approaches for automating the configuration of network security functions. These approaches seek to combine the strengths of both fields,which are formal correctness, optimization, and computational efficiency. In this paper, I present the research questions and directions that will guide my PhD activity in developing such hybrid approaches.
2025
979-8-3315-4345-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3001380