Educational Byte: Byzantine Generals Problem in Crypto —or There’s a Traitor Among Us | HackerNoon

Have you ever played Among Us? Or at least heard of it? It’s this game in which several astronauts are in the same spaceship, but a traitor is sabotaging and killing them, and they need to discover who it is and eject them from the ship. The Byzantine Generals Problem is something similar in distributed systems.

Imagine you’re playing Among Us with a bunch of friends. You’re all crewmates (and maybe some impostors) on a spaceship, and you need to decide together whether to press the emergency button to eject a suspicious player. You can only send messages to each other — no voice chat, just in-game chat. If too many players lie or get confused, the whole group might never agree on what to do — or worse, eject the wrong person.

This is basically the Byzantine Generals Problem: imagine a bunch of generals (or players) trying to agree on a battle plan (or eject vote), but some of them might be traitors (impostors) sending false messages. The good generals want to coordinate and win the battle, but they don’t know who they can trust, and they can’t all talk directly to each other. If they don’t come to the same decision, they might lose the war — or, in Among Us, lose the game.

In the world of distributed systems, the same problem happens when computers (nodes) try to agree on the same list of transactions. If some computers lie or malfunction (just like impostors), we need a system that helps all the honest nodes agree, even if a few are acting suspiciously. This is also known as Byzantine Fault, and thus, distributed systems like crypto networks must have Byzantine Fault Tolerance (BFT) to properly work.

BFT in Crypto Networks

BFT is a key concept that helps crypto networks stay reliable, even when some computers in the network act dishonestly or fail. There’s no single authority making decisions in decentralized systems, so the network has to find ways to agree on the correct version of the transaction history — even if a few participants lie, cheat, or crash. BFT is the ability of a system to still reach that shared agreement despite those issues, ensuring that everyone ends up trusting the same result.

Without BFT, bad things can happen. One of the most famous problems is called double-spending — when someone tries to use the same digital coin more than once. For example, imagine sending the same token to two different people at the same time. If the network can’t agree on which payment came first, the system becomes broken. This isn’t just a small glitch — it’s a fundamental weakness that would make digital currencies easy to exploit.

In fact, the double-spending problem is a major reason why decentralized money didn’t take off earlier. Satoshi Nakamoto directly called it out in the original Bitcoin whitepaper, highlighting it as a challenge that Bitcoin’s consensus system was designed to overcome without needing a central authority.

Consensus Mechanisms

In crypto networks, consensus mechanisms are the tools that allow a group of nodes to agree on what really happened — like who sent money to whom and when — even when some nodes might fail, act slowly, or try to cheat. These mechanisms are the heart of blockchain and DAG systems because they make sure everyone sees the same version of the ledger. They also play a crucial role in helping networks stay resilient against dishonest behavior — which is where Byzantine Fault Tolerance (BFT) comes in. A good consensus system lets honest nodes agree, no matter what a few bad actors try to do.

For example, Bitcoin uses Proof of Work (PoW). This method asks computers to solve complex puzzles to add new blocks to the chain, and powerful computers compete to be the first to solve it. The more blocks are added on top of a transaction, the less likely it is that someone could rewrite history — because of the large resources required to re-solve the puzzles — but there’s never 100% certainty. This is called probabilistic finality, which can feel a bit uncomfortable for people who expect quick and definite confirmation, especially for large payments.

In contrast, Obyte, which is built on a DAG (Directed Acyclic Graph), uses a different method. Every user approves their own transactions just by sending them, and the ordering to avoid potential double-spending relies on transactions posted by Order Providers. They’re trusted and public nodes whose transactions act as anchors that bring order to the tangle of other transactions.

Their actions lead to deterministic finality —once a transaction is stable in the DAG, it’s final and can’t be undone. There are no miners or “validators” controlling access or coming to an agreement amongst themselves. This approach, which dispenses with all kinds of voting or power competition, lends much better decentralization and censorship resistance. Thanks to this design, Obyte achieves consensus without needing energy-hungry mining or central intermediaries.

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