Yichen Liu (Indiana University Bloomington), Jingwen Yan (Clemson University), Song Liao (Texas Tech University), Long Cheng (Clemson University), Luyi Xing (Indiana University Bloomington)

Privacy compliance has become a significant concern for IoT users as the popularity of diverse IoT devices continues to grow. However, the heterogeneous nature of IoT brings challenges in designing effective privacy-preserving mechanisms. While Matter is a promising unifying connectivity protocol for IoT, it currently offers limited privacy compliance features. In this position paper, we propose the MATTERCOMPLIANCE framework, which achieves privacy compliance by design within the Matter protocol. The design of MATTERCOMPLIANCE follows three principles: providing reliable and proactive privacy disclosure for users, offering interfaces for developers to conveniently integrate privacy mechanisms, and enabling users to manage their privacy settings. By integrating privacy-preserving capabilities in the Matter protocol, MATTERCOMPLIANCE fills the gap in offering a unified solution for privacy compliance in IoT systems.

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CounterSEVeillance: Performance-Counter Attacks on AMD SEV-SNP

Stefan Gast (Graz University of Technology), Hannes Weissteiner (Graz University of Technology), Robin Leander Schröder (Fraunhofer SIT, Darmstadt, Germany and Fraunhofer Austria, Vienna, Austria), Daniel Gruss (Graz University of Technology)

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AI-Assisted RF Fingerprinting for Identification of User Devices in...

Aishwarya Jawne (Center for Connected Autonomy & AI, Florida Atlantic University), Georgios Sklivanitis (Center for Connected Autonomy & AI, Florida Atlantic University), Dimitris A. Pados (Center for Connected Autonomy & AI, Florida Atlantic University), Elizabeth Serena Bentley (Air Force Research Laboratory)

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RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial...

Dzung Pham (University of Massachusetts Amherst), Shreyas Kulkarni (University of Massachusetts Amherst), Amir Houmansadr (University of Massachusetts Amherst)

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ERW-Radar: An Adaptive Detection System against Evasive Ransomware by...

Lingbo Zhao (Institute of Information Engineering, Chinese Academy of Sciences), Yuhui Zhang (Institute of Information Engineering, Chinese Academy of Sciences), Zhilu Wang (Institute of Information Engineering, Chinese Academy of Sciences), Fengkai Yuan (Institute of Information Engineering, CAS), Rui Hou (Institute of Information Engineering, Chinese Academy of Sciences)

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