Mark Huasong Meng (National University of Singapore), Qing Zhang (ByteDance), Guangshuai Xia (ByteDance), Yuwei Zheng (ByteDance), Yanjun Zhang (The University of Queensland), Guangdong Bai (The University of Queensland), Zhi Liu (ByteDance), Sin G. Teo (Agency for Science, Technology and Research), Jin Song Dong (National University of Singapore)

Ever since its genesis, Android has enabled apps to access data and services on mobile devices. This however involves a wide variety of user-unresettable identifiers (UUIs), e.g., the MAC address, which are associated with a device permanently. Given their privacy sensitivity, Android has tightened its UUI access policy since its version 10, in response to the increasingly strict privacy protection regulations around the world. Non-system apps are restricted from accessing them and are required to use user-resettable alternatives such as advertising IDs.

In this work, we conduct a systematic study on the effectiveness of the UUI safeguards on Android phones including both Android Open Source Project (AOSP) and Original Equipment Manufacturer (OEM) phones. To facilitate our large-scale study, we propose a set of analysis techniques that discover and assess UUI access channels. Our approach features a hybrid analysis that consists of static program analysis of Android Framework and forensic analysis of OS images to uncover access channels. These channels are then tested with differential analysis to identify weaknesses that open any attacking opportunity. We have conducted a vulnerability assessment on 13 popular phones of 9 major manufacturers, most of which are top-selling and installed with the recent Android versions. Our study reveals that UUI mishandling pervasively exists, evidenced by 51 unique vulnerabilities found (8 listed by CVE). Our work unveils the status quo of the UUI protection in Android phones, complementing the existing studies that mainly focus on apps' UUI harvesting behaviors. Our findings should raise an alert to phone manufacturers and would encourage policymakers to further extend the scope of regulations with device-level data protection.

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Non-Interactive Privacy-Preserving Sybil-Free Authentication Scheme in VANETs

Mahdi Akil (Karlstad University), Leonardo Martucci (Karlstad University), Jaap-Henk Hoepman (Radboud University)

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MetaWave: Attacking mmWave Sensing with Meta-material-enhanced Tags

Xingyu Chen (University of Colorado Denver), Zhengxiong Li (University of Colorado Denver), Baicheng Chen (University of California San Diego), Yi Zhu (SUNY at Buffalo), Chris Xiaoxuan Lu (University of Edinburgh), Zhengyu Peng (Aptiv), Feng Lin (Zhejiang University), Wenyao Xu (SUNY Buffalo), Kui Ren (Zhejiang University), Chunming Qiao (SUNY at Buffalo)

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Access Your Tesla without Your Awareness: Compromising Keyless Entry...

Xinyi Xie (Shanghai Fudan Microelectronics Group Co., Ltd.), Kun Jiang (Shanghai Fudan Microelectronics Group Co., Ltd.), Rui Dai (Shanghai Fudan Microelectronics Group Co., Ltd.), Jun Lu (Shanghai Fudan Microelectronics Group Co., Ltd.), Lihui Wang (Shanghai Fudan Microelectronics Group Co., Ltd.), Qing Li (State Key Laboratory of ASIC & System, Fudan University), Jun Yu (State Key…

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Lightning Community Shout-Outs to:

(1) Jonathan Petit, Secure ML Performance Benchmark (Qualcomm) (2) David Balenson, The Road to Future Automotive Research Datasets: PIVOT Project and Community Workshop (USC Information Sciences Institute) (3) Jeremy Daily, CyberX Challenge Events (Colorado State University) (4) Mert D. Pesé, DETROIT: Data Collection, Translation and Sharing for Rapid Vehicular App Development (Clemson University) (5) Ning…

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