Special Session: Emerging Architecture Design, Control, and Security Challenges in Software Defined Vehicles

El-Fatyany, Aya; Wang, Xiaohang; Duggirala, Parasara Sridhar; Chakraborty, Samarjit; Pasricha, Sudeep; Singh, Amit Kumar

doi:10.1109/codes-isss60120.2024.00014

2024 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS) 2024

DOI: 10.1109/codes-isss60120.2024.00014

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Special Session: Emerging Architecture Design, Control, and Security Challenges in Software Defined Vehicles

Aya El-Fatyany,

Xiaohang Wang,

Parasara Sridhar Duggirala

et al.

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Tesla Log Data Analysis Approach from a Digital Forensics Perspective

Lee,

Lim,

Hyeon

et al. 2024

WEVJ

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Modern vehicles are equipped with various electronic control units (ECUs) for safety, entertainment, and autonomous driving. These ECUs operate independently according to their respective roles and generate considerable data. However, owing to capacity and security concerns, most of these data are not stored. In contrast, Tesla vehicles, equipped with multiple sensors and designed under the software-defined vehicle (SDV) concept, collect, store, and periodically transmit data to dedicated servers. The data stored inside and outside the vehicle by the manufacturer can be used for various purposes and can provide numerous insights to digital forensics researchers investigating incidents/accidents. In this study, various data stored inside and outside of Tesla vehicles are described sequentially from a digital forensics perspective. First, we identify the location and range of the obtainable storage media. Second, we explain how the data are acquired. Third, we describe how the acquired data are analyzed. Fourth, we verify the analyzed data by comparing them with one another. Finally, the cross-analysis of various data obtained from the actual accident vehicles and the data provided by the manufacturer revealed consistent trends across the datasets. Although the number of data points recorded during the same timeframe differed, the overall patterns remained consistent. This process enhanced the reliability of the vehicle data and improved the accuracy of the accident investigation.

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Tesla Log Data Analysis Approach from a Digital Forensics Perspective

Lee,

Lim,

Hyeon

et al. 2024

WEVJ

View full text Add to dashboard Cite

show abstract

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Special Session: Emerging Architecture Design, Control, and Security Challenges in Software Defined Vehicles

Cited by 1 publication

References 65 publications

Tesla Log Data Analysis Approach from a Digital Forensics Perspective

Tesla Log Data Analysis Approach from a Digital Forensics Perspective

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