Game of Trust: How Trustworthy Does Your Blockchain Think You Are?
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866909833545908224 |
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| author | Drineas, Petros Nema, Rohit Ostrovsky, Rafail Zikas, Vassilis |
| author_facet | Drineas, Petros Nema, Rohit Ostrovsky, Rafail Zikas, Vassilis |
| contents | We investigate how a blockchain can distill the collective belief of its nodes regarding the trustworthiness of a (sub)set of nodes into a {\em reputation system} that reflects the probability of correctly performing a task. To address this question, we introduce a framework that breaks it down into two sub-problems:
1. (Information Extraction): How can the system distill trust information from a function of the nodes' true beliefs?
2. (Incentive Design): How can we incentivize nodes to truthfully report such information?
To tackle the first sub-problem, we adapt, in a non-trivial manner, the well-known PageRank algorithm to our problem. For the second, we define a new class of games, called Trustworthy Reputation games (TRep games), which aim to extract the collective beliefs on trust from the actions of rational participants. We then propose a concrete TRep game whose utility function leverages Personalized PageRank and can be instantiated through a straightforward blockchain rewards mechanism. Building on this, we show how the TRep game enables the design of a reputation system. Such systems can enhance the robustness, scalability, and efficiency of blockchain and DeFi solutions. For instance, we demonstrate how such a system can be used within a Proof-of-Reputation blockchain. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_14551 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Game of Trust: How Trustworthy Does Your Blockchain Think You Are? Drineas, Petros Nema, Rohit Ostrovsky, Rafail Zikas, Vassilis Computer Science and Game Theory Artificial Intelligence Cryptography and Security We investigate how a blockchain can distill the collective belief of its nodes regarding the trustworthiness of a (sub)set of nodes into a {\em reputation system} that reflects the probability of correctly performing a task. To address this question, we introduce a framework that breaks it down into two sub-problems: 1. (Information Extraction): How can the system distill trust information from a function of the nodes' true beliefs? 2. (Incentive Design): How can we incentivize nodes to truthfully report such information? To tackle the first sub-problem, we adapt, in a non-trivial manner, the well-known PageRank algorithm to our problem. For the second, we define a new class of games, called Trustworthy Reputation games (TRep games), which aim to extract the collective beliefs on trust from the actions of rational participants. We then propose a concrete TRep game whose utility function leverages Personalized PageRank and can be instantiated through a straightforward blockchain rewards mechanism. Building on this, we show how the TRep game enables the design of a reputation system. Such systems can enhance the robustness, scalability, and efficiency of blockchain and DeFi solutions. For instance, we demonstrate how such a system can be used within a Proof-of-Reputation blockchain. |
| title | Game of Trust: How Trustworthy Does Your Blockchain Think You Are? |
| topic | Computer Science and Game Theory Artificial Intelligence Cryptography and Security |
| url | https://arxiv.org/abs/2505.14551 |