Study on did application methods for blockchain-based traffic forensic data

Cheolhee Yoon, Jaehun Hwang, Minje Cho, Bong Gyou Lee

Research output: Contribution to journalReview articlepeer-review

2 Citations (Scopus)


Traffic accident investigation has been used to reconstruct the cause and condition of the accident by using images and driving record data that introduce IT technology, and to analyze both sides of the accident, skid marks, and vehicle damage to identify the perpetrators and victims. How-ever, level 3 self-driving vehicles are the most important factor in determining the cause and impu-tation of the accident by the driver or manufacturer with control information at the time of the acci-dent. It is also developing into a network and connected vehicle with various restrictions such as the burden of the price of sensors equipped with self-driving cars and climate and rapidly changing road traffic information. In addition, network and connected vehicle driving data are stored on the outside, or various devices and sensors are installed to store information on the outside for conven-ience in operation, and efforts to enact laws are continuing. This paper attempts to propose a traffic investigation digital framework using digital data generated by these devices and sensors.

Original languageEnglish
Article number1268
Pages (from-to)1-12
Number of pages12
JournalApplied Sciences (Switzerland)
Issue number3
Publication statusPublished - 2021 Feb 1

Bibliographical note

Funding Information:
Funding: This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2020-0-00901, Information tracking technology related with cyber crime activity including illegal virtual asset transaction) Data Availability Statement: Software, python code and block chain DID in future sense platform; Data, Vehicle sensor data.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes


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