An Attribute-Based Blockchain Reputation Architecture for Counterparty Risk Assessment in Pseudonymous Transactions

Abstract

Counterparty risk in pseudonymous cryptocurrency transactions is difficult to manage using mechanisms that depend on stable legal identities, trusted intermediaries, reversible payments, or effective post-transaction dispute resolution. This conceptual paper proposes Riskonami, an attribute-based blockchain reputation architecture for pre-transaction decision support. The design separates a minimal, tamper-evident rating-event substrate from off-chain evidence, independently governed risk algorithms and wallet-level decision policies. Governance is framed as a permissioned Proof-of-Trust evidence commons: independently governed stewards preserve provenance-rich evidence and factual claims, while risk algorithms remain outside the consensus boundary. It specifies the system requirements, data placement, candidate reviewer filters, an operational confidence model and an adversarial evaluation framework. The contribution is architectural and hypothesis-generating: it does not claim that blockchain makes ratings truthful or that the proposed manipulation controls have yet been empirically validated. Rather, it identifies a design space in which persistent evidence, contextual attributes and algorithmic disagreement can support later counterparty-risk assessment before value is transferred.