Asymmetric distributed trust

A sound model for blockchain consensus with flexible and subjective trust.

Blockchain and consensus

The success of cryptocurrencies like Bitcoin and Ethereum relies on a widely shared perception that these blockchains are “trustless”. Their consensus mechanism uses proof-of-work coupled with mining rewards. They are decentralized in the sense that anyone interested may take part in the decision process, and the nodes governing the blockchain have no identities.

Different protocols for consensus (or Byzantine agreement) have been studied in science for about 40 years and traditionally rely on participant identities for voting. Many Byzantine-fault tolerant consensus algorithms have been adapted for distributing trust in blockchain systems recently: Tendermint, Hyperledger Fabric, LibraBFT and many others use consensus in this model. They may achieve 1000s of times better throughput than consensus with proof-of-work.

Since the early days of “blockchain”, many developers have sought to fill the gap between these two consensus approaches and to combine the best elements of both worlds: no voting and anonymity from proof-of-work with speed and formal correctness from Byzantine consensus. All too often, such proposals simply consisted of a white paper with no substance, however.

Marko Vukolic and I have reviewed some blockchain consensus efforts in 2017 and issued a snake-oil warning. We pointed out that blockchain consensus is like cryptography: don’t build your own! Instead, rely on established principles and formal proofs.

Consensus

Reaching consensus is not always that easy

Ripple and Stellar - consensus?

The Ripple consensus protocol (RCP) has been developed around 2014 by Ripple Labs and aims at solving the Byzantine consensus problem in a new model, where each participant node only listens to nodes that it trusts. It is claimed that RCP provides consensus, but this has been refuted by multiple researchers in the scientific literature (here and here).

The interesting idea of Ripple is to let each participant express its own, flexible trust choice. Notice that traditional Byzantine consensus protocols use only “trust by numbers” and require common trust: among the N participating nodes, every subset of F could misbehave, towards any node. Such algorithms typically achieve consensus as long as F < N/3. RCP no longer requires common trust and lets each node make its own assumption about the trustworthiness of others.

Number of votes

Stellar later evolved from Ripple and introduced its own consensus protocol, SCP, based on Federated Byzantine Quorum Systems (FBQS). SCP makes the subjective trust choice of each node more precise and aims to extend Byzantine consensus. However, existing models of Byzantine quorums and protocols cannot be generalized to FBQS.

Safety and liveness

According to a fundamental result in distributed computing, every sound protocol must satisfy safety and liveness properties:

  • Safety means that nothing “bad” will ever happen.

  • Liveness means that something “good” will happen in the future.

But algorithms that achieve only one property are useless! For example, doing nothing is always safe. Similarly, and algorithm that simply does something, even if it is wrong, is always live. (As an example, read the recent observations about Ethereum’s CBC casper).

In a paper released 2018, authors at Ripple demonstrated that RCP could violate consensus if used as intended with subjective trust. (Not surprisingly, this finding is well-hidden in the middle of their paper!) Namely, if nodes depart from the common trust configuration issued by Ripple Labs (through a “Unique Node List” in the default configuration file) and instead express their own choices, then RCP may halt and violate liveness! “Manual intervention” would then be needed to restart the network.

For Stellar’s consensus protocol, a recent study titled “Is Stellar As Secure As You Think?” has found that the subjective trust choices of the nodes made the network significantly centralized. The system does not provide the intended resilience against faults and attacks. In May 2019, the Stellar blockchain actually halted and violated liveness because not enough trustworthy nodes existed.

As of today, it remains unclear to which extent that Ripple’s and Stellar’s protocols actually provide consensus as needed by blockchains. Each system is clearly governed by their “mother” entity, company or foundation. In the mathematical sense, neither one is a consensus protocol.

No algorithms have yet filled the gap between the decentralized approach without identities and Byzantine consensus using voting. Finding models for consensus with subjective trust and flexible quorums has been a widely open question for years.

Asymmetric distributed trust

A newly published paper that Björn Tackmann of IBM Research and I co-authored answers this question. It introduces a new model for asymmetric distributed trust and formalizes Byzantine quorum systems that allow subjective trust. Every node is free to choose which combinations of other nodes it trusts or considers faulty.

Asymmetric quorum system

Our asymmetric quorum formulation extends the well-established quorum systems that underlie classic Byzantine consensus. We also introduce several protocols with asymmetric trust that strictly generalize existing standard algorithms, which have so far required common trust and knowledge of all nodes. We are currently building a full consensus protocol in this model, which will be suitable for blockchain platforms.

By allowing open membership and abandoning a shared view of trust in the system, asymmetric quorums bridge the gap between the two main consensus protocol families used by blockchains. For protocols in this model, it will be possible to formally prove safety and liveness, as necessary for understanding the security of a blockchain network. The participants will be able to clearly evaluate their voting power and to check whether given choices of “whom trusts whom” are safe for operating the network or if they carry the risk of failure.

Link to arxiv.org paper

Written on June 25, 2019