Song Liao, Jingwen Yan, Long Cheng (Clemson University)

The rapid evolution of Internet of Things (IoT) technologies allows users to interact with devices in a smart home environment. In an effort to strengthen the connectivity of smart devices across diverse vendors, multiple leading device manufacturers developed the Matter standard, enabling users to control devices from different sources seamlessly. However, the interoperability introduced by Matter poses new challenges to user privacy and safety. In this paper, we propose the Hidden Eavesdropping Attack in Matter-enabled smart home systems by exploiting the vulnerabilities in the Matter device pairing process and delegation phase. Our investigation of the Matter device pairing process reveals the possibility of unauthorized delegation. Furthermore, such delegation can grant unauthorized Matter hubs (i.e., hidden hubs) the capability to eavesdrop on other IoT devices without the awareness of device owners. Meanwhile, the implementation flaws from companies in device management complicate the task of device owners in identifying such hidden hubs. The disclosed sensitive data about devices, such as the status of door locks, can be leveraged by malicious attackers to deduce users’ activities, potentially leading to security breaches and safety issues.

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Content Censorship in the InterPlanetary File System

Srivatsan Sridhar (Stanford University), Onur Ascigil (Lancaster University), Navin Keizer (University College London), François Genon (UCLouvain), Sébastien Pierre (UCLouvain), Yiannis Psaras (Protocol Labs), Etienne Riviere (UCLouvain), Michał Król (City, University of London)

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A Duty to Forget, a Right to be Assured?...

Hongsheng Hu (CSIRO's Data61), Shuo Wang (CSIRO's Data61), Jiamin Chang (University of New South Wales), Haonan Zhong (University of New South Wales), Ruoxi Sun (CSIRO's Data61), Shuang Hao (University of Texas at Dallas), Haojin Zhu (Shanghai Jiao Tong University), Minhui Xue (CSIRO's Data61)

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Securing Lidar Communication through Watermark-based Tampering Detection (Long)

Michele Marazzi, Stefano Longari, Michele Carminati, Stefano Zanero (Politecnico di Milano)

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CAGE: Complementing Arm CCA with GPU Extensions

Chenxu Wang (Southern University of Science and Technology (SUSTech) and The Hong Kong Polytechnic University), Fengwei Zhang (Southern University of Science and Technology (SUSTech)), Yunjie Deng (Southern University of Science and Technology (SUSTech)), Kevin Leach (Vanderbilt University), Jiannong Cao (The Hong Kong Polytechnic University), Zhenyu Ning (Hunan University), Shoumeng Yan (Ant Group), Zhengyu He (Ant…

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