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Deep Fuzzy Control-Based Network Blockchain Privacy Data Protection

Author

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  • Jinfeng He

    (Nantong University, China)

  • Xixi Chen

    (Nantong University, China)

  • Zelin Wang

    (Nantong University, China)

  • Shi Cheng

    (Nantong University, China)

Abstract

Data protection is becoming more and more popular as a result of the ongoing growth of technologies like the Internet of Things and cloud computing. To better support this development, an increasing number of academics are delving further into the topic. The field of privacy protection technologies in the big data environment has steadily gained attention as data security measures have been expanded. Besides that, there are additional difficulties in safeguarding the privacy of various parties when it comes to data protection because data is frequently maintained by multiple parties. In this paper, we propose a network block chain privacy data protection scheme using depth fuzzy control. We achieve confidentiality of protected data by utilizing blockchain technology and deep fuzzy control algorithms. The deep fuzzy control method can be used in the aforementioned scheme to safeguard trading information while also enabling the interchange of protection data. Ultimately, the experiment is conducted in the context of cloud storage, and the findings validate the efficacy of the program.

Suggested Citation

  • Jinfeng He & Xixi Chen & Zelin Wang & Shi Cheng, 2024. "Deep Fuzzy Control-Based Network Blockchain Privacy Data Protection," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 18(1), pages 1-17, January.
  • Handle: RePEc:igg:jcini0:v:18:y:2024:i:1:p:1-17
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