A model for deriving trust and reputation on blockchain-based e-payment system

Abstract

E-commerce has become a crucial part of our life allowing us to buy products, request services, and transfer money easily with a press of a button. As such, establishing immutable trust and reputation of entities that are resilient to manipulation by the malicious are critical in today's online systems. In this work, we propose a model for calculating trust and reputation using the values stored on blockchain ledger. The model is applied to blockchain-based online payment systems which have a characteristic of immutability by preventing data manipulation. The model normalizes user evaluations based on each user's personal evaluation criteria that changes over time. In addition, the model derives reputation of, and trust between, users by applying psychological factors. We evaluate our model using not only simulated transaction data but also on real Bitcoin transaction-based dataset to show that our model is able to derive stable values from immutable transactions on blockchain-based online payment systems. Our model has been built into a live commercial blockchain service platform, and new application developments are underway.