Trustless Price Feeds of Cryptocurrencies: Pathfinder

TL;DR

This paper introduces a novel trustless algorithm for cryptocurrency price feeds that resists manipulation, ensuring accurate prices even with dishonest sources, and balances security with query response speed.

Contribution

It presents a new algorithmic approach for secure, trustless cryptocurrency price feeds that is resilient to manipulation and scalable in terms of speed and security.

Findings

The proposed method resists artificial price inflation by malicious sources.

It maintains accuracy of prices despite dishonest reporting sources.

The algorithm balances security and response time effectively.

Abstract

Price feeds of securities is a critical component for many financial services, allowing for collateral liquidation, margin trading, derivative pricing and more. With the advent of blockchain technology, value in reporting accurate prices without a third party has become apparent. There have been many attempts at trying to calculate prices without a third party, in which each of these attempts have resulted in being exploited by an exploiter artificially inflating the price. The industry has then shifted to a more centralized design, fetching price data from multiple centralized sources and then applying statistical methods to reach a consensus price. Even though this strategy is secure compared to reading from a single source, enough number of sources need to report to be able to apply statistical methods. As more sources participate in reporting the price, the feed gets more secure with the slowest feed becoming the bottleneck for query response time, introducing a tradeoff between security and speed. This paper provides the design and implementation details of a novel method to algorithmically compute security prices in a way that artificially inflating targeted pools has no effect on the reported price of the queried asset. We hypothesize that the proposed algorithm can report accurate prices given a set of possibly dishonest sources.