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Title:
Proof of Review (PoR): A New Consensus Protocol for Deriving Trustworthiness of Reputation Through Reviews
Authors: Zachary Zaccagni, Ram Dantu
Abstract:This paper provides a theoretical background for a new consensus model called Proof of Review (PoR), which extends Algorand’s blockchain consensus model and reproduces the human mechanism for analyzing reviews through analysis and reputation. Our protocol derives the trustworthiness of a participant’s reputation through a consensus of these reviews. In this new protocol, we combined concepts from proof of stake and proof of reputation to ensure a blockchain system comes to consensus on an honest (non-malicious) congruent review. Additionally, we formally prove this protocol provides further security by using a reputation-based stake instead of token-based, using theorems and proofs. We introduce new concepts in using reputation as a stake, where reputation must be earned and can never be purchased, spent, or traded. The stake is calculated based on the reputation – not tokens – of a user in the system proportional to the total reputation in the system at the beginning of each round. A round is a set of steps that conclude in a block being added to the blockchain. We also introduce blacklisting as a decisive action where, after a vote, an honest user will blacklist a leader (the participant elected with their proposed block) or reviewer for some egregious maliciousness, preventing further participation. Five steps are defined that overlay Algorand’s steps: (1) Evaluation of reviews; (2) Selection of the round’s leader and their associated block containing reviews; (3) Re-evaluation of reviews; (4) Block of reviews agreement (block decision); (5) Block addition to the ledger and reputation adjustment. At every step, verifiers are selected randomly for evaluating the reviews and are anonymous to each other. We provided properties related to reputation and formally proved (Honest Leader, Blacklisting Liveliness and Correctness, Evaluation of the Evaluator’s Confidence, Gradual Gain, and Swift Loss of Reputation). Finally, we discuss several types of attacks that are common for Proof of Stake and Reputation systems, and how our Proof of Review model (in extending Algorand) addresses those attacks. Furthermore, PoR mitigates several kinds of fake reviews (e.g. spam, trolling, etc.) through analysis. Preliminary experimental results show that payment transactions have similar completion times, regardless of the stake being tokens or reputation, the mechanism for adjusting reputation reflects expected behavior, and the accuracy of the review evaluation (using sentimental analysis) is substantiated for the dataset given. With this new model, we let the technology evaluate a review and secure it on a blockchain using a reputation-based stake. Proof of Review also provides third party access to reviewer’s reputation along with their respective evaluated reviews, a functionality that could benefit numerous industries including retail, academia, hospitality, corporate, and more. Applications could expedite and validate many different types of processes that rely on a form of review and the analysis of that review.
ePrint: https://eprint.iacr.org/2020/475
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