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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EMIRIS: Eavesdropping on Iris Information via Electromagnetic Side Channel

Wenhao Li (Shandong University), Jiahao Wang (Shandong University), Guoming Zhang (Shandong University), Yanni Yang (Shandong University), Riccardo Spolaor (Shandong University), Xiuzhen Cheng (Shandong University), Pengfei Hu (Shandong University)

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BrowserFM: A Feature Model-based Approach to Browser Fingerprint Analysis

Maxime Huyghe (Univ. Lille, Inria, CNRS, UMR 9189 CRIStAL), Clément Quinton (Univ. Lille, Inria, CNRS, UMR 9189 CRIStAL), Walter Rudametkin (Univ. Rennes, Inria, CNRS, UMR 6074 IRISA)

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mmProcess: Phase-Based Speech Reconstruction from mmWave Radar

Hyeongjun Choi, Young Eun Kwon, Ji Won Yoon (Korea University)

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I know what you MEME! Understanding and Detecting Harmful...

Yong Zhuang (Wuhan University), Keyan Guo (University at Buffalo), Juan Wang (Wuhan University), Yiheng Jing (Wuhan University), Xiaoyang Xu (Wuhan University), Wenzhe Yi (Wuhan University), Mengda Yang (Wuhan University), Bo Zhao (Wuhan University), Hongxin Hu (University at Buffalo)

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