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.

View More Papers

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)

Read More

Truman: Constructing Device Behavior Models from OS Drivers to...

Zheyu Ma (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University; EPFL; JCSS, Tsinghua University (INSC) - Science City (Guangzhou) Digital Technology Group Co., Ltd.), Qiang Liu (EPFL), Zheming Li (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University; JCSS, Tsinghua University (INSC) - Science City (Guangzhou) Digital Technology Group Co., Ltd.), Tingting Yin (Zhongguancun…

Read More

Lend Me Your Beam: Privacy Implications of Plaintext Beamforming...

Rui Xiao (Zhejiang University), Xiankai Chen (Zhejiang University), Yinghui He (Nanyang Technological University), Jun Han (KAIST), Jinsong Han (Zhejiang University)

Read More

Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication...

Jung-Woo Chang (University of California, San Diego), Ke Sun (University of California, San Diego), Nasimeh Heydaribeni (University of California, San Diego), Seira Hidano (KDDI Research, Inc.), Xinyu Zhang (University of California, San Diego), Farinaz Koushanfar (University of California, San Diego)

Read More