Christopher Ellis (The Ohio State University), Yue Zhang (Drexel University), Mohit Kumar Jangid (The Ohio State University), Shixuan Zhao (The Ohio State University), Zhiqiang Lin (The Ohio State University)

Wireless technologies like Bluetooth Low Energy (BLE) and Wi-Fi are essential to the Internet of Things (IoT), facilitating seamless device communication without physical connections. However, this convenience comes at a cost—exposed data exchanges that are susceptible to observation by attackers, leading to serious security and privacy threats such as device tracking. Although protocol designers have traditionally relied on strategies like address and identity randomization as a countermeasure, our research reveals that these attacks remain a significant threat due to a historically overlooked, fundamental flaw in exclusive-use wireless communication. We define _exclusive-use_ as a scenario where devices are designed to provide functionality solely to an
associated or paired device. The unique communication patterns inherent in these relationships create an observable boolean side-channel that attackers can exploit to discover whether two devices “trust” each other. This information leak allows for the deanonymization of devices, enabling tracking even in the presence of modern countermeasures. We introduce our tracking attacks as _IDBleed_ and demonstrate that BLE and Wi-Fi protocols that support confidentiality, integrity, and authentication remain vulnerable to deanonymization due to this fundamental flaw in exclusive-use communication patterns. Finally, we propose and quantitatively evaluate a generalized, privacy-preserving mitigation we call _Anonymization Layer_ to find a negligible 2% approximate overhead in performance and power consumption on tested smartphones and PCs.

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Chang Yue (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Kai Chen (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Zhixiu Guo (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Jun Dai, Xiaoyan Sun (Department of Computer Science, Worcester Polytechnic Institute), Yi Yang (Institute of Information Engineering, Chinese Academy…

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The Forking Way: When TEEs Meet Consensus

Annika Wilde (Ruhr University Bochum), Tim Niklas Gruel (Ruhr University Bochum), Claudio Soriente (NEC Laboratories Europe), Ghassan Karame (Ruhr University Bochum)

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Tao Ni (City University of Hong Kong), Yuefeng Du (City University of Hong Kong), Qingchuan Zhao (City University of Hong Kong), Cong Wang (City University of Hong Kong)

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Feedback-Guided API Fuzzing of 5G Network

Tianchang Yang (Pennsylvania State University), Sathiyajith K S (Pennsylvania State University), Ashwin Senthil Arumugam (Pennsylvania State University), Syed Rafiul Hussain (Pennsylvania State University)

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