2025, issue 3, p. 91-99
Received 02.06.2025; Revised 11.08.2025; Accepted 02.09.2025
Published 29.09.2025; First Online 30.09.2025
https://doi.org/10.34229/2707-451X.25.3.8
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A Blockchain-Based Approach to Trust System Design in Multi-Agent Environments
Andrii Dovzhenko 
, Vadym Yaremenko *
National technical university of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv
* Correspondence: This email address is being protected from spambots. You need JavaScript enabled to view it.
Introduction. This paper presents a decentralized approach to building a trust system for distributed multi-agent environments using blockchain technology. The developed system, TrustLedger, is based on Ethereum smart contracts, ERC-20 tokens, and token-weighted voting mechanisms. This approach enables transparent, secure, and scalable interactions between agents, even in scenarios with partial distrust and without centralized authority. TrustLedger includes mechanisms for agent registration, role and task creation, proposal submission, voting, token staking, and the automatic distribution of rewards and penalties. Agent reputation is built through honest participation in the system, while the influence of dishonest participants decreases as their voting power is gradually reduced. A simulation of an energy distribution scenario demonstrated the system’s ability to effectively identify and isolate malicious agents while maintaining high levels of internal trust. In contrast to centralized trust models, which are vulnerable to failures and abuse, the proposed solution provides resilience to network dynamics, latency, communication disruptions, and adversarial behavior. The advantages of smart contracts – automation, transparency, and immutability – enable “trust by design,” reducing dependence on human intervention or centralized intermediaries. The described system is a promising tool for use in smart grids, IoT environments, and collaborative robotics, where autonomous agents must interact without prior trust.
The purpose of the paper. To develop and evaluate the decentralized trust system TrustLedger for multi-agent distributed environments using blockchain technology.
Results. A prototype of the TrustLedger system was implemented, demonstrating the ability to isolate dishonest agents and maintain consensus stability. Simulation results showed a consistent reduction in the influence of malicious agents over several rounds of interaction. Agents that regularly acted against collective interest lost their reputation and voting weight, confirming the effectiveness of the incentive and penalty mechanisms.
Conclusions. The TrustLedger system has proven to be an effective decentralized solution for managing trust in multi-agent systems. By utilizing smart contracts and token-weighted voting, it enables transparency, security, and self-regulation without the need for centralized control. This approach provides a resilient environment for agent interaction, even in dynamic and potentially adversarial settings.
Keywords: multi-agent systems, distributed systems, TrustLedger, blockchain, trust system, smart contracts, ERC-20, decentralized governance, agent reputation, voting.
Cite as: Dovzhenko A., Yaremenko V. A Blockchain-Based Approach to Trust System Design in Multi-Agent Environments. Cybernetics and Computer Technologies. 2025. 3. P. 91–99. (in Ukrainian) https://doi.org/10.34229/2707-451X.25.3.8
References
1. Buterin V. ERC-20 Token Standard. Ethereum Foundation. 2014. https://eips.ethereum.org/EIPS/eip-20
2. Leonardos S., Reijsbergen D., Piliouras G. Weighted Voting on the Blockchain: Improving Consensus in Proof of Stake Protocols. 2019. IEEE International Conference on Blockchain and Cryptocurrency (ICBC). Seoul, Korea (South), 2019. P. 376–384. https://doi.org/10.1109/BLOC.2019.8751290
3. Zheng Z., Xie S., Dai H., Chen X., Wang H. An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends. In 2017 IEEE International Congress on Big Data (BigData Congress), 2018. P. 557–564. https://doi.org/10.1109/BigDataCongress.2017.85
4. Olfati-Saber R., Fax J.A., Murray R.M. Consensus and cooperation in networked multi-agent systems. Proceedings of the IEEE, 2007. 95 (1). P. 215–233. https://doi.org/10.1109/JPROC.2006.887293
5. Kamvar S.D., Schlosser M.T., Garcia-Molina H. The EigenTrust Algorithm for Reputation Management in P2P Networks. In Proceedings of the 12th International Conference on World Wide Web. 2003. P. 640–651. https://doi.org/10.1145/775152.775242
6. Grishchenko I., Maffei M., Schneidewind C. A Semantic Framework for the Security Analysis of Ethereum Smart Contracts. In Proceedings of the 30th IEEE Computer Security Foundations Symposium (CSF 2018), 2018. P. 33–47. https://doi.org/10.1109/CSF.2018.00010
7. Kiayias A., Russell A., David B., Oliynykov R. Ouroboros: A Provably Secure Proof-of-Stake Blockchain Protocol. In Annual International Cryptology Conference (CRYPTO 2017). Lecture Notes in Computer Science, Springer, 2017. Vol. 10401. P. 357–388. https://doi.org/10.1007/978-3-319-63688-7_12
ISSN 2707-451X (Online)
ISSN 2707-4501 (Print)
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