NCOG Insights

Quantum Byzantine Fault Tolerance

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Quantum Byzantine Fault Tolerance is a leading consensus mechanism that fuses quantum principles and Byzantine fault-tolerant ones to create agreement while some participants are malicious.

However, as they are, traditional Byzantine fault tolerance protocols are limited to at most only one-third of malicious nodes. We achieve these limits by combining quantum technologies, such as quantum digital signatures and verifiable secret sharing, to provide better security and fault tolerance than existing protocols.

Early development of QBFT

QBFT is based on classical Byzantine fault tolerance (BFT), an important concept in the distributed system domain, which aims at handling arbitrary failures, including malicious actors with a guarantee that the system reaches a consensus.

This work is based on the Byzantine Generals Problem, formalized in the 1980s by Leslie Lamport and colleagues. That paper, explains how a group of parties can reach a consensus even if some are not honest or reliable.

The idea of quantum advancement in fault-tolerant protocols was to find the unique properties of quantum mechanics, entanglement, and quantum superposition, to help the protocols be secure and efficient.

One such protocol is quantum Byzantine protocols which use quantum entanglement and verify secret sharing to provide secure information exchange even when some participants are at a very far distance.

Because quantum states can’t be perfectly cloned or intercepted without detection, quantum-based solutions give stronger guarantees, e.g. unconditional security in contrast to classical BFT protocols.

Quantum BFT has partly been developed to address the novel challenges in distributed systems regarding blockchain networks and quantum key distribution (QKD).

One area of progress is towards overcoming the traditional constraints put on deterministic consensus by the FLP impossibility theorem which says that a deterministic consensus is not possible even in a purely asynchronous system with at least one faulty node.

Some previous limits can be bypassed and communication overhead reduced simultaneously as system integrity is maintained in adversarial environments with quantum protocols like those incorporating verifiable quantum secret sharing (QVSS).

Today, as quantum fault tolerance research advances and as we develop more robust implementations in areas like secure multi-party computation blockchain and quantum-secured communication networks, we will see this.

Working of Quantum Byzantine Fault Tolerance

QBFT uses principles of quantum mechanics to solve the Byzantine Generals Problem where agreement is sought despite bad actors (or participants).

Here’s how it works at a high level, incorporating both classical distributed systems concepts and quantum technologies:

  1. Quantum Verifiable Secret Sharing (QVSS):
  1. Quantum Communication and Entanglement:
  1. Byzantine Agreement Protocol in a Quantum Setting:
  1. Leader Election Using Quantum Coin Flipping:
  1. Resilience Against Classical and Quantum Attacks:

Consensus Process Overview: 

Applications and Future Use

Quantum Communication Networks: 

We test QBFT protocols on small-scale quantum networks to enhance communication reliability. These networks use quantum entanglement and other quantum properties to reach consensus among nodes no matter how faulty or malicious participants are.

QBFT was recently demonstrated in multiple-use quantum communication setups for high security with no trusted central authorities.

Blockchain and Decentralized Systems: 

Blockchain technology has started showing some attention to quantum-secured consensus mechanisms. By adding quantum elements like quantum digital signatures and secure multiparty computation they improve classical Byzantine Fault Tolerance (BFT).

Distributed systems are protected from various attacks that make use of classical communication vulnerabilities. When it’s used with technologies such as IoT or edge computing, QBFT improves resilience and security in blockchain networks.

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