Abstract
We present a novel digital forensic approach that facilitates the investigation of hit-and-run accidents. Based on wheel speeds gathered by forensic data loggers, our approach provides a priority ranking of the suspects in order to optimize further investigations. For this, we propose two investigation steps to get key information about a suspect’s trip. First, we analyze the likely traveled routes of a suspect to determine whether the suspect could have been at the accident location. Second, we analyze the driving behavior of the suspect in terms of aggressiveness, since aggressive driving behavior is a major reason for traffic accidents. Our evaluation with real driving experiments shows that our approach is suitable for analyzing likely routes and driving behavior in order to prioritize suspects in an investigation.
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Notes
- 1.
A preliminary stage of this research was presented as an extended abstract at the PerCom PhD Forum 2019 [27].
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Acknowledgment
We thank the Chair of Mechatronics of the University of Duisburg-Essen and in particular Dieter Schramm for providing the Ford C-Max, which was used to evaluate our approach.
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Waltereit, M., Uphoff, M., Zdankin, P., Matkovic, V., Weis, T. (2021). A Digital Forensic Approach for Optimizing the Investigation of Hit-and-Run Accidents. In: Goel, S., Gladyshev, P., Johnson, D., Pourzandi, M., Majumdar, S. (eds) Digital Forensics and Cyber Crime. ICDF2C 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 351. Springer, Cham. https://doi.org/10.1007/978-3-030-68734-2_11
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