Accident Information Based Reliability Estimation Model for Car Insurance Smart Contract

자동차보험용 스마트 컨트랙트를 위한 사고정보 기반 신뢰도 산정 모델

  • 이수진 (한양대학교 전자공학과) ;
  • 김애영 (한양대학교 ERICA 공학기술연구소) ;
  • 서승현 (한양대학교 ERICA 캠퍼스 전자공학부)
  • Received : 2019.10.01
  • Accepted : 2019.12.26
  • Published : 2020.04.30


In order to reduce the time and cost used in insurance processing, studies have been actively carried out to apply blockchain smart contract technology to car insurance. However, by using traffic data that is insufficient to prove accidents, existing studies are being exposed to the risk of insurance fraud, such as forgery and overstated damage by malicious insurers. To solve this problem, we propose an accident data-based reliability estimation model by using both various types of data through sensors, RSUs, and IoT devices embedded in automobiles and smart contracts. In particular, the regression model was applied in consideration of the weight estimation according to the type of traffic accident data and the reliability estimation model trained according to various accident situations. The proposed model is expected to effectively reduce fraud and insurance litigation while providing transparency in the insurance process and streamlining it is well.


Supported by : IITP (Institute for Information & Communications Technology Promotion), 한국연구재단


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