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Advisor(s)
Abstract(s)
User trust is a fundamental issue in e-commerce. To address this problem, recommendation
systems have been widely used in different application domains including social media healthcare,
e-commerce, and others. In this paper, we present a systematic review of the literature in the area
of blockchain-based reputation models and we discuss the obtained results, answering the initial
research questions. These findings lead us to conclude that the existing systems are based on a trusted
third party (TTP) to collect and store reputation data, which does not provide transparency on users’
reputation scores. In the recent literature, on the one hand, blockchain-based reputation systems
have been highlighted as possible solutions to effectively provide the necessary transparency, as
well as effective identity management. On the other hand, new challenges are posed in terms of
user privacy and performance, due to the specific characteristics of the blockchain. According to the
literature, two major approaches have been proposed based on public and permissioned blockchains.
Each approach applies adjusted models for calculating reputation scores. Despite the undoubted
advantages added by a blockchain, the problem is only partially solved since there is no effective
way to prevent blockchain oracles from feeding the chain with false, unfair, or biased data. In our
future work, we intend to explore the two approaches discussed in the literature in order to propose
a new blockchain-based model for deriving user reputation scores.
Description
Keywords
Reputation system User reputation Blockchain Blockchain oracles E-commerce Security Fraud
Citation
Publisher
MDPI
Collections
CC License
Without CC licence