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Blockchain-based autonomous decentralized trust management for social network

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Abstract

In a permissionless social network environment, it is difficult for a user to assess the trustworthiness of other users. Thus, trust management becomes a crucial issue for securing social activities. The conventional method for assessing trust involves an authority to identify fakes. However, generative AI is gradually reducing the ability to distinguish by producing vivid news or images. Additionally, modern social networks are becoming flatter and more diverse, making conventional trust management methods unfeasible. There is an urgent need to design a suitable blockchain consensus for decentralized trust management. In this paper, we propose a novel three-layer autonomous trust management model for online social users based on blockchain technology and group decision making. Instead of solving a hash puzzle, which consumes too much computational resources for social network users, this paper proposes a lightweight and verifiable blockchain consensus proof of trust for decentralized trust management. Furthermore, performance analysis and simulation results show that our model is valid and flexible for both synthetic networks and real social networks.

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Availability of data and materials

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This research was funded by the University of Macau (File No. MYRG2022-00162-FST and MYRG2019-00136-FST).

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Authors and Affiliations

  1. Department of Computer and Information Science, University of Macau, Macau, China

    Qi-An Huang & Yain-Whar Si

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  1. Qi-An Huang
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  2. Yain-Whar Si
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Contributions

QH contributed to conceptualization, methodology, software, and writing—original draft preparation. Y-WS contributed to supervision, writing—reviewing and editing, and funding acquisition.

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Correspondence to Yain-Whar Si.

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Huang, QA., Si, YW. Blockchain-based autonomous decentralized trust management for social network. J Supercomput (2024). https://doi.org/10.1007/s11227-024-06024-w

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