Analyzing Privacy Implications of Data Collection in Android Automotive OS
Bulut G\"oz\"ub\"uy\"uk, Brian Tang, Kang G. Shin, Mert D. Pes\'e

TL;DR
This paper investigates the privacy implications of data collection in Android Automotive OS, revealing undisclosed data types and developing PriDrive, a tool for analyzing vehicle data privacy and policy compliance.
Contribution
It introduces PriDrive, a novel automotive privacy analysis tool combining network, static, and dynamic analysis methods for vehicle data privacy assessment.
Findings
Vehicle speed data collected at 25 Hz
Certain vehicle properties are collected without proper disclosure
OEM privacy policies cover only a fraction of collected data
Abstract
Modern vehicles have become sophisticated computation and sensor systems, as evidenced by advanced driver assistance systems, in-car infotainment, and autonomous driving capabilities. They collect and process vast amounts of data through various embedded subsystems. One significant player in this landscape is Android Automotive OS (AAOS), which has been integrated into over 100M vehicles and has become a dominant force in the in-vehicle infotainment market. With this extensive data collection, privacy has become increasingly crucial. The volume of data gathered by these systems raises questions about how this information is stored, used, and protected, making privacy a critical issue for manufacturers and consumers. However, very little has been done on vehicle data privacy. This paper focuses on the privacy implications of AAOS, examining the exact nature and scope of data collection…
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Taxonomy
TopicsEnergy and Environmental Systems · Innovation in Digital Healthcare Systems · Internet of Things and Social Network Interactions
