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Group Design02:01

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The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to...
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Related Experiment Video

Updated: May 7, 2026

Scalable Solution-processed Fabrication Strategy for High-performance, Flexible, Transparent Electrodes with Embedded Metal Mesh
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Enhancing secure multi-group data sharing through integration of IPFS and hyperledger fabric.

Feng Wen1, Zhuo Wang1, Leda Qu1

  • 1School of Information Science and Engineering, Shenyang Ligong University, Shenyang, Liaoning, China.

Peerj. Computer Science
|April 25, 2024
PubMed
Summary

This study introduces a secure multi-group data sharing network using blockchain and IPFS. It enhances data integrity and prevents key leakage for reliable peer-to-peer sharing.

Keywords:
BlockchainData integrityData sharingDynamic keyIPFSMultiple groups

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Area of Science:

  • Computer Science
  • Information Security
  • Distributed Systems

Background:

  • Data sharing faces challenges like integrity verification, encryption key leakage, and cross-group access difficulties.
  • Existing data transmission methods suffer from low security and reliability, leading to key cracking and data breaches.

Purpose of the Study:

  • To propose a novel multi-group data sharing network model for secure peer-to-peer (P2P) sharing.
  • To address the identified challenges in data integrity, encryption security, and inter-group data accessibility.

Main Methods:

  • A Consortium Blockchain and InterPlanetary File System (IPFS) based multi-group network model is proposed.
  • Dynamic key encryption algorithm, data probes for integrity verification, and Hyperledger Fabric for logging are utilized.
  • Data owners maintain complete control over data access, ensuring privacy and security.

Main Results:

  • The proposed model effectively addresses data integrity verification and encryption key leakage issues.
  • The system demonstrates secure and reliable P2P data sharing across different user groups.
  • Experimental results confirm the wide applicability and robustness of the proposed data sharing network.

Conclusions:

  • The developed model offers a secure and efficient solution for multi-group data sharing.
  • It enhances data security, integrity, and user privacy in distributed environments.
  • The system provides a scalable and reliable framework for modern data sharing needs.