Grand Theft App: Digital Forensics of Vehicle Assistant Apps
Simon Ebbers (M\"unster University of Applied Sciences), Fabian Ising, (M\"unster University of Applied Sciences), Christoph Saatjohann (M\"unster, University of Applied Sciences), Sebastian Schinzel (M\"unster University, of Applied Sciences)

TL;DR
This paper explores digital forensic analysis of vehicle assistant apps across eight manufacturers, demonstrating how smartphone and backend data can reconstruct vehicle activities for criminal investigations.
Contribution
It introduces a comprehensive forensic methodology for analyzing vehicle assistant apps, including data extraction from smartphones and manufacturer backends, to aid investigations.
Findings
Successful reconstruction of trips and refueling events
Determination of parking positions and durations
Tracking vehicle locking and unlocking events
Abstract
Due to the increasing connectivity of modern vehicles, collected data is no longer only stored in the vehicle itself but also transmitted to car manufacturers and vehicle assistant apps. This development opens up new possibilities for digital forensics in criminal investigations involving modern vehicles. This paper deals with the digital forensic analysis of vehicle assistant apps of eight car manufacturers. We reconstruct the driver's activities based on the data stored on the smartphones and in the manufacturer's backend. For this purpose, data of the Android and iOS apps of the car manufacturers Audi, BMW, Ford, Mercedes, Opel, Seat, Tesla, and Volkswagen were extracted from the smartphone and examined using digital forensic methods in accordance with lawful government-approved forensics guidelines. Additionally, manufacturer data was retrieved using Subject Access Requests. Using…
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