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Forensic Investigations in Vehicle Data Stores

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Published:14 November 2019Publication History

ABSTRACT

This research locates vehicle data stores and analyzes their forensic information value based on digital forensic principles. Four distinct data store types were located in this process -- airbag Event Data Recorder (EDR), Electronic Control Unit (ECU), Telematic Platform and Infotainment System.

Based on the analysis of approximately 11,000 samples from vehicle crashes the airbag EDR is found useful for getting a high resolution short-term snapshot of a vehicle crash. The investigated telematic platform did not store any forensically valuable data by default. Nevertheless, with an architectural optimization, it could store data valuable for both post-crime and post-crash investigations.

References

  1. National Highway Traffic Safety Administration. [n.d.]. FTP Listing of National Automotive Sampling System (NASS) EDR Reports. ftp://ftp.nhtsa.dot.gov/NASS/EDR_Reports/Google ScholarGoogle Scholar
  2. National Highway Traffic Safety Administration. [n.d.]. National Automotive Sampling System (NASS) Crash Viewer. https://crashviewer.nhtsa.dot.gov/Google ScholarGoogle Scholar
  3. National Highway Traffic Safety Administration. 2006. Final rule--event data recorders; 49 CFR Part 563. Technical Report. NHTSA.Google ScholarGoogle Scholar
  4. European Commission. 2017. Revision of the Vehicle General Safety Regulation and the Pedestrian Safety Regulation - Public consultation - Background document.Google ScholarGoogle Scholar
  5. Bosch Diagnostics. [n.d.]. CDR v17.9 System Software. https://www.boschdiagnostics.com/cdr/cdr-v179-system-softwareGoogle ScholarGoogle Scholar
  6. Gary Miller Eric S. Raymond, Chris Kuethe. [n.d.]. gpsd --- a GPS service daemon. http://www.catb.org/gpsd/Google ScholarGoogle Scholar
  7. Exponent Failure Analysis Associates. 2011. Testing and Analysis of Toyota Event Data Recorders. Technical Report.Google ScholarGoogle Scholar
  8. David Hynd and Mike McCarthy. 2014. Study on the benefits resulting from the installation of Event Data Recorders. Study for European Commission (2014).Google ScholarGoogle Scholar
  9. National Marine Electronics Association (NMEA). [n.d.]. NMEA 0183 Datensätze. http://www.nmea.de/nmea0183datensaetze.htmlGoogle ScholarGoogle Scholar
  10. Linux Man Pages. [n.d.]. User Commands -- DD(1). http://man7.org/linux/man-pages/man1/dd.1.htmlGoogle ScholarGoogle Scholar
  11. European Parliament and of the Council. 2016. Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46. Official Journal of the European Union (OJ) 59, 1--88 (2016).Google ScholarGoogle Scholar
  12. Aart Spek, Karlon Hagendoorn, Arlette Alphenaar, Wolfram Kalthoff, Ralf Buehrmann, and Joost WOLBERS. 2010. Interpretation der Fahrzeugfehlerspeichereintraege nach Verkehrsunfaellen/Interpretation of vehicle fault memory data after traffic accidents. VERKEHRSUNFALL UND FAHRZEUGTECHNIK 48, 1 (2010).Google ScholarGoogle Scholar
  13. Joe Sylve. [n.d.]. LiME Linux Memory Extractor. 504ENSICS Labs. https://github.com/504ensicsLabs/LiMEGoogle ScholarGoogle Scholar
  14. A. Theissler. 2017. Multi-class novelty detection in diagnostic trouble codes from repair shops. In 2017 IEEE 15th International Conference on Industrial Informatics (INDIN). 1043--1049. https://doi.org/10.1109/INDIN.2017.8104917Google ScholarGoogle ScholarCross RefCross Ref
  15. Ada Tsoi. 2015. The Potential of Event Data Recorders to Improve Impact Injury Assessment in Real World Crashes. Ph.D. Dissertation. Virginia Tech.Google ScholarGoogle Scholar
  16. Ada Tsoi, John Hinch, Richard Ruth, and Hampton Gabler. 2013. Validation of Event Data Recorders in High Severity Full-Frontal Crash Tests. SAE International Journal of Transportation Safety 1, 1 (2013), 76--99.Google ScholarGoogle ScholarCross RefCross Ref
  17. Ada Tsoi, Nicholas Johnson, and H. Gabler. 2014. Validation of Event Data Recorders in Side-Impact Crash Tests. SAE International Journal of Transportation Safety 2, 1 (2014), 130--164. http://www.jstor.org/stable/26169246Google ScholarGoogle ScholarCross RefCross Ref

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            cover image ACM Other conferences
            CECC 2019: Proceedings of the Third Central European Cybersecurity Conference
            November 2019
            134 pages
            ISBN:9781450372961
            DOI:10.1145/3360664

            Copyright © 2019 ACM

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 14 November 2019

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            • research-article
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            • Refereed limited

            Acceptance Rates

            CECC 2019 Paper Acceptance Rate19of35submissions,54%Overall Acceptance Rate38of65submissions,58%

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