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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security
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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security
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large part of the project is dedicated to better integrate automation into multiple facets of cyber-range operation, including the federation of infrastructures to deploy complex scenarios in multiple
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security. This project investigates how blockchain analytics and data engineering can enhance the detection of illicit activities across these decentralised and increasingly complex networks. By deploying
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to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal
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activities across these decentralised and increasingly complex networks. By deploying and advancing techniques such as machine learning, graph-based network analysis, and synthetic data generation, the project
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dependencies in a microservice-based infrastructure to identify the complex inter-dependencies among events generated by applications, services, system and network communications with as a final trace toot
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processing approach based on flow patterning to make meter scale LCEs of complex shapes and actuation modes. ALCEMIST builds on a tight synergistic collaboration between the Experimental Soft Matter Physics
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processing approach based on flow patterning to make meter scale LCEs of complex shapes and actuation modes. ALCEMIST builds on a tight synergistic collaboration between the Experimental Soft Matter Physics
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, the Greater Region, and beyond. Nearly all research projects are supported by a network of national and international partnerships, several with public or industrial stakeholders. At the University