Study Findings on Sensor Research Discussed by a Researcher at Changchun Sci-Tech University (A Blockchain and IPFS-Based Anticounterfeit Traceable Functionality of Car Insurance Claims System): Technology – Sensor Research

2023 DEC 19 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx Policy and Law Daily -- Investigators publish new report on sensor research. According to news originating from Changchun, People’s Republic of China, by NewsRx correspondents, research stated, “Due to frequent traffic accidents around the world, people often take out car insurance to mitigate their losses and receive compensation in a traffic accident.”

Funders for this research include National Science And Technology Council, Taiwan.

The news editors obtained a quote from the research from Changchun Sci-Tech University: “However, in the existing car insurance claims process, there are problems such as insurance fraud, inability to effectively track and transmit insurance data, cumbersome insurance procedures, and high insurance data storage costs. Since the immutability and traceability features of blockchain technology can prevent data manipulation and trace past data, we have used the Elliptic Curve Digital Signature Algorithm (ECDSA) to sign and encrypt car insurance data, ensuring both data integrity and security. We propose a blockchain and IPFS-based anticounterfeiting and traceable car insurance claims system to improve the above problems.”

According to the news editors, the research concluded: “We incorporate the Interplanetary File System (IPFS) to reduce the cost of storing insurance data. This study also attempts to propose an arbitration mechanism in the event of a car insurance dispute.”

For more information on this research see: A Blockchain and IPFS-Based Anticounterfeit Traceable Functionality of Car Insurance Claims System. Sensors, 2023,23(23). (Sensors - http://www.mdpi.com/journal/sensors). The publisher for Sensors is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/s23239577.

Our news journalists report that additional information may be obtained by contacting Chin-Ling Chen, School of Information Engineering, Changchun Sci-Tech University, Changchun 130600, People’s Republic of China. Additional authors for this research include Ying-Ming Zheng, Der-Chen Huang, Ling-Chun Liu, Hsing-Chung Chen.

ORCID is an identifier for authors and includes bibliographic information. The following is ORCID information for the author of this research: Chin-Ling Chen (http://orcid.org/0000-0002-4958-2043).

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