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Optimization of dynamic data traceability mechanism in Internet of Things based on consortium blockchain

Author

Listed:
  • Rui Qiao
  • Sifeng Zhu
  • Qingxian Wang
  • Jie Qin

Abstract

Internet of Things is widely used in many fields such as industry, medical care, education, and supply chain. With the participation of multi-authorized entities, a large number of dynamic data will be generated in the basic dimension of time. The operations on these data have to be safe and traceable for use in various forensics and decisions. Therefore, the key point of dynamic data security protection is to reject tampering of unauthorized users and to realize the process in evidence and tracing of the dynamic data operation. In order to find a solution to the problem above, an optimization of dynamic data traceability mechanism based on consortium blockchain is proposed in this article. First, a mathematical model for the security of dynamic data storage has been established, followed by analysis on honest behavior motive of individual node decision-making in group game and distributed node cooperation essence in specific industry background. After that, ownership transition function and the architecture of the dynamic data storage system are optimized; quality and growth characteristics of the system under stochastic state model are analyzed. Result shows that the solution can effectively avoid potential attacks such as tampering and faking under approved accession mode. The mechanism has good application value while ensuring the dynamic data storage security.

Suggested Citation

  • Rui Qiao & Sifeng Zhu & Qingxian Wang & Jie Qin, 2018. "Optimization of dynamic data traceability mechanism in Internet of Things based on consortium blockchain," International Journal of Distributed Sensor Networks, , vol. 14(12), pages 15501477188, December.
    • Handle: RePEc:sae:intdis:v:14:y:2018:i:12:p:1550147718819072
    DOI: 10.1177/1550147718819072
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    References listed on IDEAS

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    1. Sikorski, Janusz J. & Haughton, Joy & Kraft, Markus, 2017. "Blockchain technology in the chemical industry: Machine-to-machine electricity market," Applied Energy, Elsevier, vol. 195(C), pages 234-246.
    2. Lee, Jongkuk & Palekar, Udatta S. & Qualls, William, 2011. "Supply chain efficiency and security: Coordination for collaborative investment in technology," European Journal of Operational Research, Elsevier, vol. 210(3), pages 568-578, May.
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    Cited by:

    1. Arpaci, Ibrahim, 2023. "Predictors of financial sustainability for cryptocurrencies: An empirical study using a hybrid SEM-ANN approach," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    2. Antonello Cammarano & Vincenzo Varriale & Francesca Michelino & Mauro Caputo, 2023. "Blockchain as enabling factor for implementing RFID and IoT technologies in VMI: a simulation on the Parmigiano Reggiano supply chain," Operations Management Research, Springer, vol. 16(2), pages 726-754, June.

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