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Forensic Investigation of An Android Jellybean-based Car Audio Video Navigation System

Published: 30 July 2024 Publication History

Abstract

Recently, in-vehicle infotainment (IVI) systems, also called car audio video navigation (AVN) systems hold a wealth of digital data valuable for forensic investigations, encompassing navigation history, call logs, and Bluetooth connections. They serve as central hubs for entertainment, communication, and navigation, storing crucial evidence for accidents, thefts, and cybercrimes. Therefore, forensic investigations of IVI systems are becoming increasingly important. In this paper, we conduct a forensic analysis of an Android Jellybean-based AVN system installed in Kia K5 2017. We first efficiently collect system logs as well as navigation logs using the log menu of an engineering mode provided by the car manufacturer company. Therefore, our data collection method does not require a chip-off technique or rooting of the AVN system. Next, we analyze the collected logs systematically and the differences between the two types of log data. Our forensic investigation method can provide insights into occupant activities and reconstruct events leading to incidents and car crimes.

References

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2013. Hyundai, Kia line up Android-based infotainment systems. (2013). https://www.automotiveworld.com/articles/android-based-infotainment-systems-feature-hyundai-kia-models/ Accessed: May 10, 2024.
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William Bortles, Sean McDonough, Connor Smith, and Michael Stogsdill. 2017. An introduction to the forensic acquisition of passenger vehicle infotainment and telematics systems data. Technical Report. SAE Technical Paper.
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Kevin Klaus Gomez Buquerin, Christopher Corbett, and Hans-Joachim Hof. 2021. A generalized approach to automotive forensics. Forensic Science International: Digital Investigation 36 (2021), 301111.
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Ammar Dawabsheh and Majdi Owda. 2023. In-Vehicles Infotainment System Forensics Case Study. In 2023 International Conference on Information Technology (ICIT). IEEE, 32–37.
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Daniel Jacobs, Kim-Kwang Raymond Choo, M-Tahar Kechadi, and Nhien-An Le-Khac. 2017. Volkswagen car entertainment system forensics. In 2017 IEEE Trustcom/BigDataSE/ICESS. IEEE, 699–705.
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Haein Kang, Hojun Seong, Ilkyu Kim, Wookjae Jeong, Seong-Je Cho, Minkyu Park, and Sangchul Han. 2023. Android-Based Audio Video Navigation System Forensics: A Case Study. Applied Sciences 13, 10 (2023), 6176.
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Jesse Lacroix. 2017. Vehicular infotainment forensics: collecting data and putting it into perspective. Ph. D. Dissertation.
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  1. Forensic Investigation of An Android Jellybean-based Car Audio Video Navigation System

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      cover image ACM Other conferences
      ARES '24: Proceedings of the 19th International Conference on Availability, Reliability and Security
      July 2024
      2032 pages
      ISBN:9798400717185
      DOI:10.1145/3664476
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 30 July 2024

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      Author Tags

      1. Android
      2. Audio Video Navigation
      3. Jellybean
      4. Navigation log
      5. System log
      6. Vehicle forensics

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      • Research-article
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      Funding Sources

      • Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT
      • Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MIST)

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      ARES 2024

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      Overall Acceptance Rate 228 of 451 submissions, 51%

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