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A trustable architecture over blockchain to facilitate maritime administration for MASS systems

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  • Wang, Yang
  • Chen, Peng
  • Wu, Bing
  • Wan, Chengpeng
  • Yang, Zaili

Abstract

Maritime Autonomous Surface Ship (MASS) is widely deemed as the future of global shipping. The cyber vulnerability has however been identified as an emerging problem and a potential barrier influencing MASS development. This paper, through the investigation of the fundamental trust problem with regards to the cyber security of MASS systems, aims to develop a blockchain-based scheme for the trust management of MASS. The innovative idea of using blockchain within the MASS context is that the mobile entities in the MASS operational environment constitute a decentralized opportunity network, which makes blockchain an appealing tool to provide a solution to evaluating and maximizing the trust over the dynamics of the entities. This paper elaborates the mechanism by which the MASS entities participate in keeping the main chain. Firstly, the paper illustrates how the Belief of Trust (BoT) among the entities is encoded and assembled into the chain, to allow MASS entities to have an initial judgement towards another entity before they get acquainted. Secondly, at the consensus layer of blockchain technique, it addresses how the witness, who has a temporary right of producing a block and append it to the chain, can be elected among the nodes and how to incent the nodes to maintain the blockchain from a proof-of-stake perspective. Finally, this paper describes how the MASS entities can use the certificate dependence information to evaluate the trust transition in the MASS operating environment. Typical scenarios are delineated to show the procedure of certificate inquiry, handover of controls between maritime supervision centers and shore-side remote control centers in case of the occurrence of unexpected events. The findings provide any entity in an MASS network with an effective solution to evaluating the degree of trust he can have for any targeted node/participant. They can therefore help choose better (more trustable) nodes to maintain the MASS network's knowledge of evidence to judge the trust on an unknown member.

Suggested Citation

  • Wang, Yang & Chen, Peng & Wu, Bing & Wan, Chengpeng & Yang, Zaili, 2022. "A trustable architecture over blockchain to facilitate maritime administration for MASS systems," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    • Handle: RePEc:eee:reensy:v:219:y:2022:i:c:s0951832021007249
    DOI: 10.1016/j.ress.2021.108246
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    Cited by:

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    2. Cheng, Tingting & Utne, Ingrid Bouwer & Wu, Bing & Wu, Qing, 2023. "A novel system-theoretic approach for human-system collaboration safety: Case studies on two degrees of autonomy for autonomous ships," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    3. Guo, Yunlong & Jin, Yongxing & Hu, Shenping & Yang, Zaili & Xi, Yongtao & Han, Bing, 2023. "Risk evolution analysis of ship pilotage operation by an integrated model of FRAM and DBN," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    4. Chan, Hau-Ling & Choi, Tsan-Ming & Mendez De la Torre, Daniela, 2023. "The “SMARTER” framework and real application cases of blockchain," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    5. Bolbot, Victor & Kulkarni, Ketki & Brunou, Päivi & Banda, Osiris Valdez & Musharraf, Mashrura, 2022. "Developments and research directions in maritime cybersecurity: A systematic literature review and bibliometric analysis," International Journal of Critical Infrastructure Protection, Elsevier, vol. 39(C).
    6. Wang, Yang & Ye, Ting & Zio, Enrico & Wang, Tengfei & Wu, Bing, 2024. "A blockchain-based credibility evaluation scheme for navigational event dissemination in the internet of ships," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    7. Cheng, Tingting & Veitch, Erik A. & Utne, Ingrid Bouwer & Ramos, Marilia A. & Mosleh, Ali & Alsos, Ole Andreas & Wu, Bing, 2024. "Analysis of human errors in human-autonomy collaboration in autonomous ships operations through shore control experimental data," Reliability Engineering and System Safety, Elsevier, vol. 246(C).

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