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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Heimdall: Towards Risk-Aware Network Management Outsourcing

Yuejie Wang (Peking University), Qiutong Men (New York University), Yongting Chen (New York University Shanghai), Jiajin Liu (New York University Shanghai), Gengyu Chen (Carnegie Mellon University), Ying Zhang (Meta), Guyue Liu (Peking University), Vyas Sekar (Carnegie Mellon University)

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Privacy Preserved Integrated Big Data Analytics Framework Using Federated...

Sarah Kaleem (Prince Sultan University, PSU) Awais Ahmad (Imam Mohammad Ibn Saud Islamic University, IMSIU), Muhammad Babar (Prince Sultan University, PSU), Goutham Reddy Alavalapati (University of Illinois, Springfield)

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