Distributed Consensus with Byzantine Fault Tolerance via Quantum Key Distribution
Jincheng Zhang
Abstract
This paper proposes a novel approach to distributed consensus that leverages quantum key distribution (QKD) for Byzantine fault tolerance. Traditional consensus algorithms struggle to guarantee agreement in the face of malicious actors introducing Byzantine faults. This work introduces a framework where a shared secret, established via QKD, serves as the foundation for a consensus protocol. The inherent cryptographic properties of QKD – specifically its ability to detect eavesdropping – are exploited to identify and neutralize malicious nodes attempting to disrupt the consensus process. We demonstrate that this combination offers a fundamentally more secure and efficient solution compared to classical approaches. The core of our system relies on the creation of a quantum-secured shared key, denoted as *K*, and the subsequent implementation of a consensus protocol designed to operate on this key. This protocol incorporates mechanisms for key verification and anomaly detection, providing robust resilience against Byzantine faults. The theoretical analysis presented highlights the advantages of this approach in terms of security and efficiency. We define the following key variables: *n* - number of nodes in the network; *f* - maximum number of faulty nodes; *m* - number of correct nodes; *si* - the state of node *i* (1 if active, 0 if faulty); *K* - the quantum key shared among the nodes; *ri,j* - the raw key shared between nodes *i* and *j*; *Ei,j* - the error rate observed between nodes *i* and *j* during QKD; *σi,j* - the quantum state used for key exchange between nodes *i* and *j*; *Ci,j* - the ciphertext generated during the QKD process; *Di,j* - the decrypted ciphertext between nodes *i* and *j*; *Hi,j* - the hash value calculated based on the decrypted ciphertext. The system's robustness is directly proportional to the level of security provided by QKD and the effectiveness of the consensus protocol in detecting and isolating faulty nodes.