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Lecture notes in computer science

Error Reconciliation in Quantum Key Distribution Protocols

Miralem Mehić, Marcin Niemiec, Harun Šiljak, Miroslav Vozn̆ák

Published Jan 1, 2020• 46 citations
Publisher

Abstract

Abstract Quantum Key Distribution (QKD) protocols allow the establishment of symmetric cryptographic keys up to a limited distance at limited rates. Due to optical misalignment, noise in quantum detectors, disturbance of the quantum channel or eavesdropping, an error key reconciliation technique is required to eliminate errors. This chapter analyses different key reconciliation techniques with a focus on communication and computing performance. We also briefly describe a new approach to key reconciliation techniques based on artificial neural networks.

DOI
10.1007/978-3-030-47361-7_11

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Abstract Quantum Key Distribution (QKD) protocols allow the establishment of symmetric cryptographic keys up to a limited distance at limited rates. Due to optical misalignment, noise in quantum detectors, disturbance of the quantum channel or eavesdropping, an error key reconciliation technique is required to eliminate errors. This chapter analyses different key reconciliation techniques with a focus on communication and computing performance. We also briefly describe a new approach to key reconciliation techniques based on artificial neural networks.
Abstract In quantum cryptography, secret communications are delivered through a quantum channel. One of the most important breakthroughs in quantum cryptography has been the quantum key distribution (QKD). This process enables two distant parties to share secure communications based on physical laws. However, eavesdroppers can still interrupt the communication. To overcome this, we propose a different way to detect the presence of Eve through the polynomial interpolation technique. This technique also allows us for key verification. This approach prevents the receiver as well as the intruder from discovering the sender’s fundamental basis. To fully utilize IBM quantum computers’ quantum computing capabilities, this paper attempts to show % error against alpha (strength of eavesdropping) and the impact of noise on the success probability of the desired key bits. Furthermore, the success probability under depolarizing noise is explained for different qubit counts. In the enhanced QKD protocol, using polynomial interpolation for reconciliation shows a 50% probability of successful key generation. This is even when the noise is increased to the maximum capacity.
Intensive work on quantum computing has increased interest in quantum cryptography in recent years. Although this technique is characterized by a very high level of security, there are still challenges that limit the widespread use of quantum key distribution. One of the most important problems remains secure and effective mechanisms for the key distillation process. This article presents a new idea for a key reconciliation method in quantum cryptography. This proposal assumes the use of mutual synchronization of artificial neural networks to correct errors occurring during transmission in the quantum channel. Users can build neural networks based on their own string of bits. The typical value of the quantum bit error rate does not exceed a few percent; therefore, the strings are similar and also users’ neural networks are very similar at the beginning of the learning process. It has been shown that the synchronization process in the new solution is much faster than in the analogous scenario used in neural cryptography. This feature significantly increases the level of security because a potential eavesdropper cannot effectively synchronize their own artificial neural networks in order to obtain information about the key. Therefore, the key reconciliation based on the new idea can be a secure and efficient solution.
Quantum key distribution (QKD) relies on quantum and classical procedures in order to achieve the growing of a secret random string -the key- known only to the two parties executing the protocol. Limited intrinsic efficiency of the protocol, imperfect devices and eavesdropping produce errors and information leakage from which the set of measured signals -the raw key- must be stripped in order to distill a final, information theoretically secure, key. The key distillation process is a classical one in which basis reconciliation, error correction and privacy amplification protocols are applied to the raw key. This cleaning process is known as information reconciliation and must be done in a fast and efficient way to avoid cramping the performance of the QKD system. Brassard and Salvail proposed a very simple and elegant protocol to reconcile keys in the secret-key agreement context, known as Cascade, that has become the de-facto standard for all QKD practical implementations. However, it is highly interactive, requiring many communications between the legitimate parties and its efficiency is not optimal, imposing an early limit to the maximum tolerable error rate. In this paper we describe a low-density parity-check reconciliation protocol that improves significantly on these problems. The protocol exhibits better efficiency and limits the number of uses of the communications channel. It is also able to adapt to different error rates while remaining efficient, thus reaching longer distances or higher secure key rate for a given QKD system.
Quantum key distribution (QKD) relies on quantum and classical procedures in order to achieve the growing of a secret random string -the key- known only to the two parties executing the protocol. Limited intrinsic efficiency of the protocol, imperfect devices and eavesdropping produce errors and information leakage from which the set of measured signals -the raw key- must be stripped in order to distill a final, information theoretically secure, key. The key distillation process is a classical one in which basis reconciliation, error correction and privacy amplification protocols are applied to the raw key. This cleaning process is known as information reconciliation and must be done in a fast and efficient way to avoid cramping the performance of the QKD system. Brassard and Salvail proposed a very simple and elegant protocol to reconcile keys in the secret-key agreement context, known as Cascade, that has become the de-facto standard for all QKD practical implementations. However, it is highly interactive, requiring many communications between the legitimate parties and its efficiency is not optimal, imposing an early limit to the maximum tolerable error rate. In this paper we describe a low-density parity-check reconciliation protocol that improves significantly on these problems. The protocol exhibits better efficiency and limits the number of uses of the communications channel. It is also able to adapt to different error rates while remaining efficient, thus reaching longer distances or higher secure key rate for a given QKD system.
Information Security is of paramount importance in digital communication in today’s highly networked world. Conventional information security methods face many future threats, one being the likelihood of large scale Quantum Computation. Quantum Cryptography is coming to the fore in the field of information security. It is all about using quantum physics to perform the cryptographic tasks as well as to break cryptographic systems. There are recent many advancements in the quantum cryptography field like Quantum Coin Flipping, Quantum Bit Commitment, and Quantum Key Distribution (QKD) networks. In this paper, a new concept for error correction and key reconciliation method is presented that uses Artificial Neural Network (ANN) with the help of Tree Parity Machine (TPM). In our work, we have considered a few cases of TPMs synchronization process with specific values of Quantum Bit Error Rate(QBER) and have performed some comparison among those. The experimental results observed into this paper that prove the correctness of the proposed work.
Quantum key distribution (QKD) is a secure communication technique that uses quantum mechanical principles. This method enables two trusted users to exchange a secret key or message securely by exploiting the fundamental properties of quantum mechanics. Strong long-distance secure communication is provided by QKD but its effectiveness is mainly limited by quantum bit error rate (QBER), finite-key effects, and the effectiveness of classical error-correction during information reconciliation. In this work, we proposes a neural-aided adaptive reconciliation (NAAR) framework based on artificial neural networks for QKD that integrates a lightweight neural belief propagation decoder with QBER-driven adaptive LDPC coderate selection. By lowering frame-error rate and information leakage, neural-assisted log-likelihood ratio calibration enhances belief-propagation convergence for binary symmetric channels. The result shows an improvement in secret key rates (SKR) and lower error rates over traditional LDPC-based reconciliation.