In our paper we present interactions between artificial intelligence (AI) and the field of cybersecurity. We present work of the Horizon Europe CS-AWARE-NEXT project that aims to provide improved cybersecurity management capabilities to organisations and local/ regional supply networks. Such organisations and networks operate in a highly dynamic cybersecurity environment, and must comply with European legislation such as the network and information security (NIS/NIS2) directive. Organisations increasingly understand that cybersecurity needs to be more dynamic and collaborative, building on a shared situational awareness of potential cybersecurity issues relevant to the organisations and networks in question. There is no doubt that there exists a cybersecurity shortfall in many organisations as the majority of their legacy systems have not been designed either to foster cybersecurity awareness, nor are they Artificial Intelligence / Machine Learning-ready, in terms of permitting models and algorithms to be deployed, or to interact with the application logic of the original systems. To remedy this, there is a need for experimenting with novel approaches to information systems engineering that can address needs emerging from the inclusion of dedicated Artificial Intelligence and Machine Learning modules and components to enable provisions for self-healing, self-protecting, and self-configuration.

Addressing Critical Issues and Challenges for Dynamic Cybersecurity Management in Organisations and Local/Regional Networks: The CS-AWARE-NEXT Project

Cappiello C.;
2023-01-01

Abstract

In our paper we present interactions between artificial intelligence (AI) and the field of cybersecurity. We present work of the Horizon Europe CS-AWARE-NEXT project that aims to provide improved cybersecurity management capabilities to organisations and local/ regional supply networks. Such organisations and networks operate in a highly dynamic cybersecurity environment, and must comply with European legislation such as the network and information security (NIS/NIS2) directive. Organisations increasingly understand that cybersecurity needs to be more dynamic and collaborative, building on a shared situational awareness of potential cybersecurity issues relevant to the organisations and networks in question. There is no doubt that there exists a cybersecurity shortfall in many organisations as the majority of their legacy systems have not been designed either to foster cybersecurity awareness, nor are they Artificial Intelligence / Machine Learning-ready, in terms of permitting models and algorithms to be deployed, or to interact with the application logic of the original systems. To remedy this, there is a need for experimenting with novel approaches to information systems engineering that can address needs emerging from the inclusion of dedicated Artificial Intelligence and Machine Learning modules and components to enable provisions for self-healing, self-protecting, and self-configuration.
2023
Proceedings - 2023 5th International Conference on Transdisciplinary AI, TransAI 2023
Business Continuity
Corpo-rate Information Infrastructures
Critical Infrastructure Protection
Cybersecurity Management
Disaster Recovery
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1261162
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