Skip to main content

A Smart Contract-Based Risk Warning Blockchain Symbiotic System for Cross-border Products

  • Conference paper
  • First Online:
Advances in E-Business Engineering for Ubiquitous Computing (ICEBE 2019)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 41))

Included in the following conference series:

Abstract

In the current supervision mode of cross-border products, the government supervises insufficiently due to incomplete and untrustworthy risk data, non-autonomous and human intervened risk evaluation models. A smart contract-based risk warning blockchain symbiotic system is proposed to reform the issues of the current system. The system is a new third-party system that provides risk warning data services for the government. A permissioned blockchain ecosystem has been developed to provide open, equal, and credible services for the government and enterprises. A risk warning model is implemented by smart contracts to provide a non-intervention evaluation for cross-border products. The autonomy of the system is realized through smart contracts such as enterprise access audit, risk data acquisition, risk assessment and feedback. The system effectively improves the science and intelligence of supervision, cut down the customs clearance time and sampling proportion, and has been verified in the Administration of Inspection and Quarantine in Shanghai Airport.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Adviser of the UK Government Chief Scientific: Distributed ledger technology: beyond block chain, January 2016

    Google Scholar 

  2. Alharby, M., van Moorsel, A.: Blockchain-based smart contracts: a systematic mapping study. arXiv preprint arXiv:1710.06372 (2017)

  3. Barley, M.: Samsung SDS to create Korean customs blockchain, September 2018. https://www.ledgerinsights.com/samsung-sds-creates-korean-customs-blockchain/

  4. Dai, Y.: A research on a planning on entry-exit inspection and quarantine conformity conditions screening and inspection & risk pre-warning. Doctor , Nanjing University of Science and Technology (2009)

    Google Scholar 

  5. Feng, W., Huang, J.: Early warning for civil aviation security checks based on deep learning. Data Anal. Knowl. Discovery 2(10), 46–53 (2018)

    Google Scholar 

  6. General Administration of Quality Supervision, Inspection and Quarantine: Circular of the general administration of quality inspection and quarantine on publishing measures for credit management of entry-exit inspection and quarantine enterprises. http://www.gov.cn/gongbao/content/2013/content_2509242.htm

  7. Hyperledger: Hyperledger Composer Docs

    Google Scholar 

  8. IBM: Blockchain basics: Hyperledger Fabric, July 2018

    Google Scholar 

  9. Kim, B., Hong, S.C., Egger, D., Katsar, C.S., Griffin, R.L.: Predictive modeling and categorizing likelihoods of quarantine pest introduction of imported propagative commodities from different countries. Risk Anal. 39(6), 1382–1396 (2019)

    Article  Google Scholar 

  10. Liu, J., Jiang, P., Leng, J.: A framework of credit assurance mechanism for manufacturing services under social manufacturing context. In: 2017 13th IEEE Conference on Automation Science and Engineering (CASE), pp. 36–40, August 2017

    Google Scholar 

  11. Saadaoui, Z.: Digitization of ATA Carnets: how the Blockchain could enhance trust

    Google Scholar 

  12. Santamaria, S.C.: CADENA, a blockchain enabled solution for the implementation of mutual recognition Arrangements/agreements

    Google Scholar 

  13. Shenzhen OneConnetc Smart Technology Co., Ltd and Ping An Blockchain Research Institute: Blockchain Whitepaper For Cross-border Trade, Feburary 2019

    Google Scholar 

  14. Xiao, H.: Ensemble learning models and algorithms for risk decision-making problems. Doctor, Chongqing University (2017)

    Google Scholar 

  15. Yu, Y.: Mining and analysising of chongqing customs’ import and export data. Master, Chongqing University (2008)

    Google Scholar 

  16. Yuan, C., Xu, Y.: Research on implementing classified inspection supervision for export mechanical and electrical products. Modern Commod. Inspection Sci. Tech. (05), 7–9+17 (2001)

    Google Scholar 

  17. Zhou, X., Zhang, C.: Customs risk classification and forecasting model based on data mining. J. Customs Trade 38(02), 22–31 (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yinsheng Li .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wu, B., Li, Y., Liang, X. (2020). A Smart Contract-Based Risk Warning Blockchain Symbiotic System for Cross-border Products. In: Chao, KM., Jiang, L., Hussain, O., Ma, SP., Fei, X. (eds) Advances in E-Business Engineering for Ubiquitous Computing. ICEBE 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 41. Springer, Cham. https://doi.org/10.1007/978-3-030-34986-8_20

Download citation

Publish with us

Policies and ethics