Automatic, location-privacy preserving dashcam video sharing using blockchain and deep learning View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2020-08-26

AUTHORS

Taehyoung Kim, Im Y. Jung, Yih-Chun Hu

ABSTRACT

Today, many people use dashcams, and videos recorded on dashcams are often used as evidence of accident fault. People can upload videos of dashcam recordings with specific accident clips and share the videos with others who request them, by providing the time or location of an accident. However, dashcam videos are erased when the dashcam memory is full, so periodic backup is necessary for video sharing. It is inconvenient for dashcam owners to search for and transmit a requested video clip from backup videos. In addition, anonymity is not ensured, which may reduce location privacy by exposing the video owner’s location. To solve this problem, we propose a video sharing scheme with accident detection using deep learning coupled with automatic transfer to the cloud; we also propose ensuring data and operational integrity along with location privacy by using blockchain smart contracts. Furthermore, our proposed system uses proxy re-encryption to enhance the confidentiality of a shared video. Our experiments show that our proposed automatic video sharing system is cost-effective enough to be acceptable for deployment. More... »

PAGES

36

References to SciGraph publications

  • 2017-09-04. Privacy-preserving blockchain-based electric vehicle charging with dynamic tariff decisions in SICS SOFTWARE-INTENSIVE CYBER-PHYSICAL SYSTEMS
  • 2018-10-12. Classifying 3D objects in LiDAR point clouds with a back-propagation neural network in HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES
  • <error retrieving object. in <ERROR RETRIEVING OBJECT
  • 2020-03-17. A blockchain-based smart home gateway architecture for preventing data forgery in HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES
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    http://scigraph.springernature.com/pub.10.1186/s13673-020-00244-8

    DOI

    http://dx.doi.org/10.1186/s13673-020-00244-8

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