A Biologically Inspired Trust Model for Open Multi-Agent Systems That Is Resilient to Rapid Performance Fluctuations
Trust management provides an alternative solution for securing open, dynamic, and distributed multi-agent systems, where conventional cryptographic methods prove to be impractical. However, existing trust models face challenges such as agent mobility, which causes agents to lose accumulated trust wh...
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MDPI AG
2025-05-01
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| Online Access: | https://www.mdpi.com/2076-3417/15/11/6125 |
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| author | Zoi Lygizou Dimitris Kalles |
| author_facet | Zoi Lygizou Dimitris Kalles |
| author_sort | Zoi Lygizou |
| collection | DOAJ |
| description | Trust management provides an alternative solution for securing open, dynamic, and distributed multi-agent systems, where conventional cryptographic methods prove to be impractical. However, existing trust models face challenges such as agent mobility, which causes agents to lose accumulated trust when moving across networks; changing behaviors, where previously reliable agents may degrade over time; and the cold start problem, which hinders the evaluation of newly introduced agents due to a lack of prior data. To address these issues, we introduced a biologically inspired trust model in which trustees assess their own capabilities and store trust data locally. This design improves mobility support, reduces communication overhead, resists disinformation, and preserves privacy. Despite these advantages, prior evaluations revealed the limitations of our model in adapting to provider population changes and continuous performance fluctuations. This study proposes a novel algorithm, incorporating a self-classification mechanism for providers to detect performance drops that are potentially harmful for service consumers. The simulation results demonstrate that the new algorithm outperforms its original version and FIRE, a well-known trust and reputation model, particularly in handling dynamic trustee behavior. While FIRE remains competitive under extreme environmental changes, the proposed algorithm demonstrates greater adaptability across various conditions. In contrast to existing trust modeling research, this study conducts a comprehensive evaluation of our model using widely recognized trust model criteria, assessing its resilience against common trust-related attacks while identifying strengths, weaknesses, and potential countermeasures. Finally, several key directions for future research are proposed. |
| format | Article |
| id | doaj-art-e5f85b412ed348a8af449a529414bebb |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-e5f85b412ed348a8af449a529414bebb2025-08-20T03:46:52ZengMDPI AGApplied Sciences2076-34172025-05-011511612510.3390/app15116125A Biologically Inspired Trust Model for Open Multi-Agent Systems That Is Resilient to Rapid Performance FluctuationsZoi Lygizou0Dimitris Kalles1School of Science & Technology, Hellenic Open University, 26 335 Patra, GreeceSchool of Science & Technology, Hellenic Open University, 26 335 Patra, GreeceTrust management provides an alternative solution for securing open, dynamic, and distributed multi-agent systems, where conventional cryptographic methods prove to be impractical. However, existing trust models face challenges such as agent mobility, which causes agents to lose accumulated trust when moving across networks; changing behaviors, where previously reliable agents may degrade over time; and the cold start problem, which hinders the evaluation of newly introduced agents due to a lack of prior data. To address these issues, we introduced a biologically inspired trust model in which trustees assess their own capabilities and store trust data locally. This design improves mobility support, reduces communication overhead, resists disinformation, and preserves privacy. Despite these advantages, prior evaluations revealed the limitations of our model in adapting to provider population changes and continuous performance fluctuations. This study proposes a novel algorithm, incorporating a self-classification mechanism for providers to detect performance drops that are potentially harmful for service consumers. The simulation results demonstrate that the new algorithm outperforms its original version and FIRE, a well-known trust and reputation model, particularly in handling dynamic trustee behavior. While FIRE remains competitive under extreme environmental changes, the proposed algorithm demonstrates greater adaptability across various conditions. In contrast to existing trust modeling research, this study conducts a comprehensive evaluation of our model using widely recognized trust model criteria, assessing its resilience against common trust-related attacks while identifying strengths, weaknesses, and potential countermeasures. Finally, several key directions for future research are proposed.https://www.mdpi.com/2076-3417/15/11/6125computational trust modelsopen multi-agent systemsbiologically inspired algorithmsproviders’ dynamic behaviorcomprehensive evaluation |
| spellingShingle | Zoi Lygizou Dimitris Kalles A Biologically Inspired Trust Model for Open Multi-Agent Systems That Is Resilient to Rapid Performance Fluctuations Applied Sciences computational trust models open multi-agent systems biologically inspired algorithms providers’ dynamic behavior comprehensive evaluation |
| title | A Biologically Inspired Trust Model for Open Multi-Agent Systems That Is Resilient to Rapid Performance Fluctuations |
| title_full | A Biologically Inspired Trust Model for Open Multi-Agent Systems That Is Resilient to Rapid Performance Fluctuations |
| title_fullStr | A Biologically Inspired Trust Model for Open Multi-Agent Systems That Is Resilient to Rapid Performance Fluctuations |
| title_full_unstemmed | A Biologically Inspired Trust Model for Open Multi-Agent Systems That Is Resilient to Rapid Performance Fluctuations |
| title_short | A Biologically Inspired Trust Model for Open Multi-Agent Systems That Is Resilient to Rapid Performance Fluctuations |
| title_sort | biologically inspired trust model for open multi agent systems that is resilient to rapid performance fluctuations |
| topic | computational trust models open multi-agent systems biologically inspired algorithms providers’ dynamic behavior comprehensive evaluation |
| url | https://www.mdpi.com/2076-3417/15/11/6125 |
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