Tolga O. Atalay (A2 Labs LLC), Tianyuan Yu (UCLA), Lixia Zhang (UCLA), Angelos Stavrou (A2 Labs LLC)

Cellular core networks are deployed as a set of Virtual Network Functions (VNFs) to dynamically provide customized connectivity for specific use cases. These VNFs are software-based applications whose trust management and security rely on well-established network domain solutions and certificate-based trust mechanisms. As VNFs are frequently redeployed, migrated, and scaled across a diverse ecosystem, the reliance on static trust solutions introduces bottlenecks and operational complexities. This approach to trust undermines the ability to ensure seamless, secure, and efficient interactions in a rapidly evolving cellular ecosystem. Addressing these challenges necessitates a fundamental shift toward an architectural foundation that inherently embeds security and trust into the communication fabric. Named Data Networking (NDN) offers such a foundation by focusing on data-centric security, where trust is embedded within the data itself rather than being dependent on external entities or channels. Leveraging named entities, NDN makes it possible to construct fine-grained trust relationships across cellular domains, tenants, and network slices. This paradigm shift enables the cellular core to move beyond static security solutions, providing a cohesive and scalable framework for managing trust in next-generation cellular networks. In this paper, we propose the adoption of the NDN network model to address the limitations of traditional approaches and achieve seamless security that evolves with the dynamic demands of 5G and beyond networks.

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Eric Pauley (University of Wisconsin–Madison), Kyle Domico (University of Wisconsin–Madison), Blaine Hoak (University of Wisconsin–Madison), Ryan Sheatsley (University of Wisconsin–Madison), Quinn Burke (University of Wisconsin–Madison), Yohan Beugin (University of Wisconsin–Madison), Engin Kirda (Northeastern University), Patrick McDaniel (University of Wisconsin–Madison)

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Fabian Rauscher (Graz University of Technology), Carina Fiedler (Graz University of Technology), Andreas Kogler (Graz University of Technology), Daniel Gruss (Graz University of Technology)

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VoiceRadar: Voice Deepfake Detection using Micro-Frequency and Compositional Analysis

Kavita Kumari (Technical University of Darmstadt), Maryam Abbasihafshejani (University of Texas at San Antonio), Alessandro Pegoraro (Technical University of Darmstadt), Phillip Rieger (Technical University of Darmstadt), Kamyar Arshi (Technical University of Darmstadt), Murtuza Jadliwala (University of Texas at San Antonio), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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