IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v14y2018i12p1550147718819072.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147718819072
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1550147718819072?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alev Ozer Torgaloz & Mehmet Fatih Acar & Cemil Kuzey, 2023. "The effects of organizational learning culture and decentralization upon supply chain collaboration: analysis of covid-19 period," Operations Management Research, Springer, vol. 16(1), pages 511-530, March.
    2. Ivanov, Dmitry & Sokolov, Boris, 2013. "Control and system-theoretic identification of the supply chain dynamics domain for planning, analysis and adaptation of performance under uncertainty," European Journal of Operational Research, Elsevier, vol. 224(2), pages 313-323.
    3. Tandon, Anushree & Kaur, Puneet & Mäntymäki, Matti & Dhir, Amandeep, 2021. "Blockchain applications in management: A bibliometric analysis and literature review," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    4. Byeongtae Ahn, 2022. "Implementation and Early Adoption of an Ethereum-Based Electronic Voting System for the Prevention of Fraudulent Voting," Sustainability, MDPI, vol. 14(5), pages 1-16, March.
    5. Shengmin Tan & Xu Wang & Chuanwen Jiang, 2019. "Privacy-Preserving Energy Scheduling for ESCOs Based on Energy Blockchain Network," Energies, MDPI, vol. 12(8), pages 1-16, April.
    6. Wang, Lu & Gu, Wei & Wu, Zhi & Qiu, Haifeng & Pan, Guangsheng, 2020. "Non-cooperative game-based multilateral contract transactions in power-heating integrated systems," Applied Energy, Elsevier, vol. 268(C).
    7. Yuki Matsuda & Yuto Yamazaki & Hiromu Oki & Yasuhiro Takeda & Daishi Sagawa & Kenji Tanaka, 2021. "Demonstration of Blockchain Based Peer to Peer Energy Trading System with Real-Life Used PHEV and HEMS Charge Control," Energies, MDPI, vol. 14(22), pages 1-12, November.
    8. Young-Gyun Ahn & Taeil Kim & Bo-Ram Kim & Min-Kyu Lee, 2022. "A Study on the Development Priority of Smart Shipping Items—Focusing on the Expert Survey," Sustainability, MDPI, vol. 14(11), pages 1-21, June.
    9. Peyman Akhavan & Maryam Philsoophian, 2023. "Improving of Supply Chain Collaboration and Performance by Using Block Chain Technology as a Mediating Role and Resilience as a Moderating Variable," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(4), pages 4561-4582, December.
    10. Chand Bhatt, Priyanka & Kumar, Vimal & Lu, Tzu-Chuen & Daim, Tugrul, 2021. "Technology convergence assessment: Case of blockchain within the IR 4.0 platform," Technology in Society, Elsevier, vol. 67(C).
    11. Guilherme Luz Tortorella & Flavio S. Fogliatto & Michel J. Anzanello & Alejandro Mac Cawley Vergara & Roberto Vassolo & Jose Arturo Garza-Reyes, 2023. "Modeling the impact of industry 4.0 base technologies on the development of organizational learning capabilities," Operations Management Research, Springer, vol. 16(3), pages 1091-1104, September.
    12. Jian Wang & Qianggang Wang & Niancheng Zhou & Yuan Chi, 2017. "A Novel Electricity Transaction Mode of Microgrids Based on Blockchain and Continuous Double Auction," Energies, MDPI, vol. 10(12), pages 1-22, November.
    13. Anna Adamik & Michał Nowicki & Andrius Puksas, 2022. "Energy Oriented Concepts and Other SMART WORLD Trends as Game Changers of Co-Production—Reality or Future?," Energies, MDPI, vol. 15(11), pages 1-38, June.
    14. Silvia H. Bonilla & Helton R. O. Silva & Marcia Terra da Silva & Rodrigo Franco Gonçalves & José B. Sacomano, 2018. "Industry 4.0 and Sustainability Implications: A Scenario-Based Analysis of the Impacts and Challenges," Sustainability, MDPI, vol. 10(10), pages 1-24, October.
    15. Lu Xu & Yanhui Li & Qi Yao, 2022. "Information security investment and purchase decision for personalized products," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 2619-2635, September.
    16. Seong-Kyu Kim & Jun-Ho Huh, 2018. "A Study on the Improvement of Smart Grid Security Performance and Blockchain Smart Grid Perspective," Energies, MDPI, vol. 11(8), pages 1-22, July.
    17. Gourisetti, Sri Nikhil Gupta & Sebastian-Cardenas, D. Jonathan & Bhattarai, Bishnu & Wang, Peng & Widergren, Steve & Borkum, Mark & Randall, Alysha, 2021. "Blockchain smart contract reference framework and program logic architecture for transactive energy systems," Applied Energy, Elsevier, vol. 304(C).
    18. Tseng, Fang-Mei & Palma Gil, Eunice Ina N. & Lu, Louis Y.Y., 2021. "Developmental trajectories of blockchain research and its major subfields," Technology in Society, Elsevier, vol. 66(C).
    19. Paul, Jomon A. & Zhang, Minjiao, 2021. "Decision support model for cybersecurity risk planning: A two-stage stochastic programming framework featuring firms, government, and attacker," European Journal of Operational Research, Elsevier, vol. 291(1), pages 349-364.
    20. Meennapa Rukhiran & Songwut Boonsong & Paniti Netinant, 2024. "Sustainable Optimizing Performance and Energy Efficiency in Proof of Work Blockchain: A Multilinear Regression Approach," Sustainability, MDPI, vol. 16(4), pages 1-38, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:intdis:v:14:y:2018:i:12:p:1550147718819072. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.