Artificial Intelligence Methods for Enhancing Trustworthiness in Mobile Networks (IGEL-AI)
The objective of the project is to improve the trustworthiness of future sixth-generation (6G) mobile communication networks. The project focuses in particular on enhancing the security of 6G systems. This is to be supported, among other approaches, through the use of methods from the fields of machine learning (ML) and artificial intelligence (AI). AI-based techniques are applied both in the area of attack prevention and in attack detection. The project develops solutions across all network layers, starting from the physical transmission layer. A cross-layer security approach is pursued that takes into account the interactions between individual layers and their associated security mechanisms, with the
goal of creating a layer-spanning, efficient, and optimized overall security concept. The developed solutions are to be implemented within the project as proof-of-concept implementations and demonstrated using selected use cases.
The contributions of TU Dresden focus in particular on AI-based key generation by exploiting channel characteristics at the physical transmission layer. Both point-to-point key exchange schemes and group key exchange schemes are investigated. Depending on the deployment environment, channel characteristics differ, which in turn affects the key generation rate as well as the selection and parameterization of the algorithms required to enable efficient and secure key exchange. Artificial intelligence methods support this process, among other aspects, by automating the adaptation of these parameters to the specific deployment environment.
© Nils Eisfeld
Chair of Privacy and Security
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TUD Dresden University of Technology
Faculty of Computer Science
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Chair of Privacy and Security
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