Fault-Proofing Crypto Transactions: Explaining Byzantine Fault Tolerance

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Fault-Proofing Crypto Transactions: Explaining Byzantine Fault Tolerance Fault-Proofing Crypto Transactions: Explaining Byzantine Fault Tolerance

There’s no screening process for nodes aiming to plug into permissionless blockchains. As long as new node operators meet the software and hardware qualifications to join a chain’s consensus model, they’re free to hook up a mining rig, download the payment ledger, or start staking coins to process crypto transactions. 

This system makes blockchains like Bitcoin (BTC) transparent, accessible, and decentralized, but it also opens the possibility for serious security issues. So how can developers behind an open-source blockchain trust their validators will behave honestly, and what happens if a node suddenly decides to go rogue? 

Thanks to a game theory brain teaser, Bitcoin’s pseudonymous creator, Satoshi Nakamoto, cracked the code to ensure nodes on decentralized networks play by the rules. To this day, Nakamoto’s Byzantine fault tolerance (BFT) remains an essential component of blockchain security, helping keep crypto transactions both trustless and trustworthy. Let’s find out what BFT is, how it works, and why it’s a central aspect of decentralized currencies. 

What is Byzantine fault tolerance in crypto?

BFT is a proposed solution to a thought experiment called the Byzantine Generals’ Problem. Introduced in the '80s by computer scientists Leslie Lamport, Robert Shostak, and Marshall Pease, the problem imagines a scenario where Byzantine generals have to decide whether to attack or retreat from a fortress, but each commanding officer is in a different location and has to send messages via their lieutenants. The “problem” in this theoretical puzzle is getting all generals to act in unison while avoiding issues like delays, forged documents, or lost messages. 

So, is there a way to ensure everyone reaches the same decision despite the risk of bad actors or communication malfunctions? 

In terms of blockchain technology, the Byzantine generals symbolize validator nodes on the decentralized payment network. A cryptocurrency protocol relies on these nodes to compute, broadcast, and verify genuine transactions before posting them. However, since there aren’t central authorities screening crypto transactions, an alternative decentralized computer system to ensure data accuracy is required. 

A BFT protocol has the necessary cryptographic infrastructure to counter the communication breakdowns of the Byzantine Generals’ Problem, including malicious node operators and technical errors. While a BFT blockchain isn’t immune to Byzantine attacks, it has safety standards to make it unlikely any synchronization issues will cause severe disruptions. With a solid Byzantine consensus algorithm, cryptocurrencies continue operating even when some nodes experience technical difficulties or try to submit false transaction data—provided the majority of validators remain honest. 

How does Byzantine fault tolerance work?

In 1999, computer scientists Miguel Castro and Barbara Liskov introduced the first functional algorithm to solve the Byzantine Generals’ Problem called Practical Byzantine fault tolerance (PBFT). 

In this system, an algorithm chooses a leader node to propose a new data block and request votes from the community. The leader only commits this information to the official ledger if at least two-thirds of participating nodes vote in the block’s favor. PBFT was the first practical application of Byzantine fault tolerance but suffers from limited scalability. As more nodes join a PBFT network, it becomes exponentially less efficient due to the algorithm’s fixed voting structure.  

Some limited and privately managed blockchains use PBFT as their core algorithm, but many of today’s permissionless cryptocurrencies use one of two BFT algorithms: proof-of-work (PoW) or proof-of-stake (PoS). Both systems have significant differences but allow blockchain developers to achieve Byzantine fault tolerance without sacrificing scalability. 

PoW consensus mechanism

First introduced in the 2008 Bitcoin whitepaper, PoW consensus involves nodes solving advanced computational puzzles in predetermined time frames to win the chance to validate a new transaction data block. Node operators use their electricity on these blockchains to collect network fees and mint (or mine) some of the blockchain’s native cryptocurrency into their crypto wallet. To ensure trustworthiness on the blockchain, other nodes verify the transaction data a winning validator posts before it’s published on the official payment ledger

For example, on the Bitcoin blockchain, miners compete every 10 minutes to solve an algebraic equation using cryptographic hash functions. The first miner to figure out the correct input value, which produces the PoW algorithm’s output, submits the latest transaction to the community for review. If enough other nodes agree this transaction is correct, the winning miner receives BTC block rewards and network fees. 

A defining feature of PoW consensus is its heavy reliance on computational energy to validate transaction data. On the positive side, the high electricity requirements on PoW blockchains make them more resistant to attacks since malicious actors need to show proof of their computer’s work to submit transaction data. 

However, the high energy requirements on PoW blockchains like Bitcoin, Dogecoin (DOGE), and Litecoin (LTC) make them the least eco-friendly solution to the Byzantine Generals’ Problem. 

PoS consensus mechanism 

PoS is a greener alternative to PoW mining, where nodes stake cryptocurrency on-chain to secure the network and get a chance to participate in transaction validation. Not only do stakers have a financial incentive in the form of crypto collateral, but they also receive rewards every time the PoS algorithm chooses them to submit a new block of transactions. 

PoS validators need to download a blockchain’s payment history and constantly run their computers to broadcast transfers, but they use significantly less energy than the PoW model. PoS blockchains also tend to have greater speed and scalability than PoW blockchains since they aren’t as reliant on hardware and often have built-in governance processes like decentralized autonomous organizations (DAOs) to vote on updates.

On the downside, algorithms on PoS blockchains often give validators staking the largest amounts of cryptocurrency higher odds of confirming transactions. Critics of PoS argue this model gives large token holders an unfair advantage and introduces a vulnerability to network consensus. PoS stakers who invest in large quantities of tokens have more significant sway over network governance and consensus, potentially opening the possibility for centralization and voter manipulation. 

Why is Byzantine fault tolerance essential in crypto?

Think of a BFT algorithm as a blockchain’s armor against malicious attacks and false transaction data. With a robust Byzantine fault-tolerant system, cryptocurrencies can recognize, withstand, and deter bad actors and inaccurate transaction data, which ensures the integrity of the details in an immutable payment ledger. 

If cryptocurrencies don’t have BFT mechanisms in place, they’ll place extreme trust in the integrity of each node to always tell the truth, making it easier for a malicious minority to potentially compromise the entire network with fraudulent transactions. 

Does Byzantine fault tolerance have limitations? 

BFT is a critical component in a blockchain’s security infrastructure, but just because a cryptocurrency is fault tolerant doesn’t mean it’s “faultless.” BFT chains are more tolerant of malicious attacks, but corrupt nodes can still take over a decentralized network. 

For example, if nodes collude to take over 51% of a cryptocurrency’s blockchain—either through generating more than 50% of a PoW blockchain’s energy or staking most of the crypto on a PoS chain—they can manipulate payment data. Although 51% attacks are unlikely as blockchains grow larger and more decentralized, they have happened on smaller blockchains like Ethereum Classic (ETC) and Bitcoin SV (BSV). 

Sybil attacks, in which malicious actors create multiple fake identities to confuse a blockchain’s communication pathways, are another potential threat to BFT protocols. Like 51% attacks, successful Sybil attacks aren’t as effective as chains grow and become more decentralized, but they are a potential strategy bad actors use to confuse honest nodes. 

Beyond potential security risks, BFT algorithms have scalability challenges, especially as network activity rises and the number of nodes increases. Since BFT algorithms run on a pre-established set of codes to enforce rules without third parties, changing these rigid requirements on a whim without risking network security is impossible. 

As more people use a BFT protocol, blockchains often run into congestion issues, leading to transaction delays, higher gas fees, and an overall poor user experience. Determining how to balance the security and decentralization of BFT systems with scalability is a central concern in the cryptocurrency development community––often called the blockchain trilemma. 

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