Quantum Bit Error Rate Analysis in BB84 Quantum Key Distribution: Measurement, Statistical Estimation, and Eavesdropping Detection

TL;DR

This paper systematically reviews and analyzes the Quantum Bit Error Rate (QBER) in BB84 quantum key distribution, comparing estimation methods, examining eavesdropping detection, and discussing protocol enhancements for secure quantum communication.

Contribution

It provides a comprehensive analysis of QBER calculation, estimation techniques, and protocol improvements, including simulation and experimental insights, for enhancing BB84 security.

Findings

QBER increases linearly with eavesdropping intensity, reaching 25% under intercept-resend attacks.

Four confidence interval methods are compared for finite-key QBER estimation, highlighting their robustness.

Protocol enhancements like decoy states and hybrid cryptography improve error mitigation and security.

Abstract

Quantum Key Distribution (QKD) provides information-theoretic security by exploiting the principles of quantum mechanics. Among QKD protocols, the BB84 scheme remains the most widely adopted for both theoretical research and practical implementation. A critical parameter determining the reliability and security of BB84 is the Quantum Bit Error Rate (QBER), which quantifies errors in the sifted key arising from channel noise or potential eavesdropping. This paper presents a systematic review and analysis of QBER within the BB84 protocol, examining its calculation, statistical estimation methods, and role in detecting eavesdropping activity. Simulation results, corroborated by reported experimental observations, reveal a near-linear relationship between eavesdropping intensity and QBER, with values approaching 25% under full intercept-resend attacks. Four confidence interval estimation methods, Wald, Wilson, Clopper-Pearson, and Hoeffding's inequality, are compared for robust QBER analysis in finite-key scenarios. Protocol enhancements, including decoy-state methods, hybrid cryptographic models, and quantum-resistant authentication, are discussed as mechanisms to mitigate errors and strengthen resilience across fiber, free-space, underwater, and satellite QKD systems. Open challenges in distinguishing noise-induced errors from malicious eavesdropping, and the role of adaptive error correction and machine-learning-assisted QBER estimation in future quantum networks, are identified as key directions for further research.