Multiple Domain Security Awareness for Factories of the Future
Communications in Computer and Information Science, ISSN: 1865-0937, Vol: 1678 CCIS, Page: 29-40
2022
- 2Citations
- 14Captures
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Conference Paper Description
In the context of factory digitization, the focus of Industry 4.0 initiative is to leverage the automation and data exchange in manufacturing processes using automation, IoT, and advanced technologies. Industry 5.0 has emerged as the next industrial revolution, to adopt a human-centric approach for digital technologies. That said, having people, robots, smart machines, and intelligent production systems working together raises challenges in terms of monitoring and securing the production environment. In other words, the complexity of smart factories makes it possible for incidents to occur and interrupt the manufacturing process. They might also cause leaking sensitive information or putting the worker’s life in danger as well. Accordingly, designing secure architectures in intelligent factories is crucial to secure a continuous production lifecycle and safe working conditions. Nonetheless, due to the decentralized environment of modern factories, creating multi-domain data correlation is crucial to obtain universal monitoring of the occurring events, as well as to establish cyber situational awareness and adopt suitable countermeasures in case of attacks. For these purposes, we developed a holistic multi-domain security and safety mechanism for Factories of the Future. Our approach consists of individual but integrated modules, each of which is responsible for capturing alerts from different domains of the factory. Alerts are then handled by an intelligent correlator to inspect possible attacks or malfunctions on the investigated shop floor. In this paper, we describe the architecture and design of the developed approach.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85141691631&origin=inward; http://dx.doi.org/10.1007/978-3-031-18697-4_3; https://link.springer.com/10.1007/978-3-031-18697-4_3; https://dx.doi.org/10.1007/978-3-031-18697-4_3; https://link.springer.com/chapter/10.1007/978-3-031-18697-4_3
Springer Science and Business Media LLC
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