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

Vision: Retiring Scenarios — Enabling Ecologically Valid Measurement in...

Oliver D. Reithmaier (Leibniz University Hannover), Thorsten Thiel (Atmina Solutions), Anne Vonderheide (Leibniz University Hannover), Markus Dürmuth (Leibniz University Hannover)

Read More

Unleashing the Power of Generative Model in Recovering Variable...

Xiangzhe Xu (Purdue University), Zhuo Zhang (Purdue University), Zian Su (Purdue University), Ziyang Huang (Purdue University), Shiwei Feng (Purdue University), Yapeng Ye (Purdue University), Nan Jiang (Purdue University), Danning Xie (Purdue University), Siyuan Cheng (Purdue University), Lin Tan (Purdue University), Xiangyu Zhang (Purdue University)

Read More

On-demand RFID: Improving Privacy, Security, and User Trust in...

Youngwook Do (JPMorganChase and Georgia Institute of Technology), Tingyu Cheng (Georgia Institute of Technology and University of Notre Dame), Yuxi Wu (Georgia Institute of Technology and Northeastern University), HyunJoo Oh(Georgia Institute of Technology), Daniel J. Wilson (Northeastern University), Gregory D. Abowd (Northeastern University), Sauvik Das (Carnegie Mellon University)

Read More

An Empirical Study on Fingerprint API Misuse with Lifecycle...

Xin Zhang (Fudan University), Xiaohan Zhang (Fudan University), Zhichen Liu (Fudan University), Bo Zhao (Fudan University), Zhemin Yang (Fudan University), Min Yang (Fudan University)

Read More