Introduction

White labeling prevention is a special case of the problem of getting off-chain information on-chain in a decentralized manner. Several methods have been proposed to address this problem, generally falling under the headings of decentralized oracles, prediction markets, and decentralized justice protocols. In this note, we summarize the results of our analysis of a number of these methods as applicable to the case of white labeling prevention. We conclude that decentralized justice protocols constitute the best approach for the task at hand.

Decentralized oracles

A blockchain oracle is any mechanism for bringing off-chain data on-chain. The simplest way to do this is to have one party post the data on-chain, but that makes the party in question a single point of failure. Thus decentralized oracles are any method of posting data in a decentralized matter.

Notable examples

Some notable examples that were analyzed in our survey (or in a previous phase of our research) include:

  1. Chainlink 2.0: Next Steps in the Evolution of Decentralized Oracle Networks: It allows blockchains to leverage a Decentralized Oracle Network (DON) to pull off-chain data on-chain. These oracle networks rely on staking and economic incentives so that each of its nodes reports data truthfully
  2. DECO and Town Crier: The components are designed to allow a Prover to obtain data from a web server and present it to a Verifier in a way that ensures integrity and confidentiality. They can operate with any existing TLS-enabled server.
  3. UMA Protocol: An optimistic oracle that securely allows for arbitrary types of data to be brought on-chain. UMA leverages token holders as an integrated dispute arbitration system to this end, and could arguably be categorized as a decentralized justice protocol as well. In the linked note, an article presenting a comparison between UMA and a decentralized justice protocol is presented.
  4. NEST: Utilizes a crypto-economic game of arbitrage between its participants to provide decentralized price feeds to smart contracts.
  5. Oraclize/Provable: Instead of relying on consensus, it provides proof of authenticity (by leveraging ****TLSNotary) of all data it provides to smart contracts.
  6. TLS-N: Also allows the transfer of data behind a TLS connection to a smart contract, with proof of its authenticity. However, it requires modifications on the web server end.

Problems with using oracles

With the exception of UMA, the dedicated oracle systems mentioned above work best for on-chaining objective facts that can be readily verified by anyone who cares to. They’re less compatible with questions that require nontrivial amounts of research or subjective judgment—exactly the situations we expect with white-label resistance disputes.

Prediction markets

A decentralized prediction market (DPM) is where people can bet on binary outcomes of future events. Those who forecast the outcomes correctly win money, and those who forecast incorrectly lose money. For an introduction, consult What Are Prediction Markets: Explained For Beginners.

Intuitively, the prices of binary options in prediction markets can be interpreted as the mean belief of traders. For a detailed, quantitative account of this fact, see the article Interpreting Prediction Market Prices as Probabilities.

Examples: Presidential Elections, Sports, crypto price prediction, etc.

Source: Augur whitepaper: https://arxiv.org/pdf/1501.01042.pdf

Source: Augur whitepaper: https://arxiv.org/pdf/1501.01042.pdf