Quantum Key Distribution (QKD) is a secure communication method that uses quantum mechanics to exchange secret keys. Currently, the QKD process uses a static error correction method, which can lead to inaccuracies and inefficient resource use. The project aims to develop a new QKD error correction method that adapts dynamically based on real-time Quantum Bit Error Rate (QBER) measurements and Software Defined Networking (SDN) principles. Two specific error correction mechanisms, the 2D Parity check and the Cascade Protocol, will be used to match the QBER value. The investigation will be conducted using the DARPAN application, providing a quantum-enabled environment.
Quantum Key Distribution (QKD) is a secure communication method that uses quantum mechanics to exchange secret keys. Currently, the QKD process uses a static error correction method, which can lead to inaccuracies and inefficient resource use. The project aims to develop a new QKD error correction method that adapts dynamically based on real-time Quantum Bit Error Rate (QBER) measurements and Software Defined Networking (SDN) principles. Two specific error correction mechanisms, the 2D Parity check and the Cascade Protocol, will be used to match the QBER value. The investigation will be conducted using the DARPAN application, providing a quantum-enabled environment.
Quantum Key Distribution (QKD) is a pivotal technology in the quest for secure communication, harnessing the power of quantum mechanics to ensure robust data protection. However, scaling QKD to meet the demands of high-speed, real-world applications remains a significant challenge. Traditional key rate determination methods, dependent on complex mathematical models, often fall short in efficiency and scalability. In this paper, we propose an approach that involves integrating machine learning (ML) techniques with the Cascade error correction protocol to enhance the scalability and efficiency of QKD systems. Our ML-based approach utilizes an autoencoder framework to predict the Quantum Bit Error Rate (QBER) and final key length with over 99\% accuracy. This method significantly reduces error correction time, maintaining a consistently low computation time even with large input sizes, such as data rates up to 156 Mbps. In contrast, traditional methods exhibit exponentially increasing computation times as input sizes grow, highlighting the superior scalability of our ML-based solution. Through comprehensive simulations, we demonstrate that our method not only accelerates the error correction process but also optimizes resource utilization, making it more cost-effective and practical for real-world deployment. The Cascade protocol's integration further enhances system security by dynamically adjusting error correction based on real-time QBER observations, providing robust protection against potential eavesdropping. Our research establishes a new benchmark for scalable, high-throughput QKD systems, proving that machine learning can significantly advance the field of quantum cryptography. This work continues the evolution towards truly scalable quantum communication.
The ability to protect information has always played an important role in the evolution of civilizations, and even in the history of mankind as a whole. Safe and reliable communications have become an essential component of people’s lives in the era of modern digital technologies, when all spheres and areas of activity, from defense and government to business and social communications, are unthinkable without real-time data exchange. Classical methods of cryptographic protection have long been used to ensure the security of data transmission, but with the explosive growth in computing power and the emerging development of quantum computers, many traditional solutions have become vulnerable. Quantum Key Distribution (QKD) is a popular research area at the moment, due to its use of the laws of quantum mechanics, and thus it is possible to provide a completely secure level of encryption. But traditional quantum communication protocols have their limitations, including low key generation rates, scalability problems in large networks, and vulnerabilities to various forms of cyberattacks in the network layer. Therefore, in this work we propose a new adaptive quantum key distribution algorithm using software-defined networking (SDN) technology. The main idea of the proposed approach is to introduce some level of redundancy in the key generation stage, which increases the throughput, robustness, and adaptability of multi-node quantum networks. In addition, the SDN control layer allows dynamic routing and resource management and quick response to changes in the network state, making the system more resistant to denial-of-service and eavesdropping attacks. Evaluating our solution in comparison with BB84, we show that the new algorithm provides better performance without losing its security level, making the work a step towards creating a working quantum-secure communication system.
The current public key infrastructure (pki) encryption/decryption methods are still vulnerable to attacks. The main issue is, the public key algorithm suffers no effective solutions which are natural within particular integer factorization, distinct logarithm and also elliptic curve interactions. It might be computationally possible for an individual to create public and private key set computationally for attacking purposes. The current single channel quantum key distribution (qkd) technique suffers high quantum bit error rates (qber) in the presence of eavesdropping attacks. Therefore this high error rate needs to be reduced for better security using two channels qkd. With the current emergence of quantum computers many security algorithm that could take classical computer years to break could now be broken in matter of seconds. Therefore stronger quantum cryptography is needed for high security networking. This paper is proposed to provide a way for solving the key transmission issues using qkd, as a new method, by providing two quantum channels to improve qber. In addition also to develop an algorithm for integrating pki and qkd in solving the secrete key sharing issues in grid environment. The research methodology will require the use of qkd devices to be placed at the end of the sender and the receiver nodes for quantum channel secrete key sharing. The outcome of the research shall provide highly enhanced network cryptography mechanism for cyber security.
Error correction is a crucial stage in quantum key distribution (QKD) protocols—a promising field of modern cryptography where the secrecy of the shared key information is guaranteed by the laws of quantum mechanics. Currently, there are many effective approaches to error correction in QKD. However, most of them, due to their generic nature, fail to leverage the specific features of particular protocol implementations. This work demonstrates that accounting for the hardware specifics of a QKD system implementing the time-bin protocol enables a significant increase in error correction performance. For the considered QKD system, we have experimentally obtained estimates of the Quantum Bit Error Rate (QBER) observed for each combination of bit and detector. The differences in the obtained estimates reveal that the quantum channel can be modeled as a non-uniform binary channel. Furthermore, based on computational experiments with a model of the quantum channel, it was established that adapting the error correction procedure to its properties can achieve up to a 2.7-fold reduction in the LDPC code decoding failure rate at low error levels.
Today’s networks are quickly evolving toward more dynamic and flexible infrastructures and architectures. This software-based evolution has seen its peak with the development of the software-defined networking (SDN) and network functions virtualization (NFV) paradigms. These new concepts allow operators to automate the setup of services, thus reducing costs in deploying and operating the required infrastructure. On the other hand, these novel paradigms expose new vulnerabilities, as critical information travels through the infrastructure from central offices, down to remote data centers and network devices. Quantum key distribution (QKD) is a state-of-the-art technology that can be seen as a source of symmetric keys in two separated domains. It is immune to any algorithmic cryptanalysis and is thus suitable for long-term security. This technology is based on the laws of physics, which forbids us from copying the quantum states exchanged between two endpoints from which a secret key can be extracted. Thus, even though it has some limitations, a correct implementation can deliver keys of the highest security. In this paper, we propose the integration of QKD systems with well-known protocols and methodologies to secure the network’s control plane in an SDN and NFV environment. Furthermore, we experimentally demonstrate a workflow where QKD keys are used together with classically generated keys to encrypt communications between cloud and SDN platforms for setting up a service via secure shell, while showcasing the applicability to other cryptographic protocols.
The rapid evolution of digital infrastructure has raised significant concerns about the security of data transmission, particularly with the advent of quantum computing. Traditional cryptographic algorithms are vulnerable to attacks, highlighting the need for quantum-resistant solutions. This paper presents the integration of Quantum Key Distribution (QKD) with Software-Defined Networking (SDN) and network slicing to build a secure, programmable, and flexible network architecture. QKD ensures unconditional security based on quantum mechanics by enabling key distribution with the ability to detect eavesdropping through quantum bit error rates (QBER). SDN provides centralized control and real-time traffic management, while network slicing allows isolation, reliability and customization of traffic flows for specific applications such as URLLC, eMBB, and mMTC. When abnormal QBER or decryption failures are detected, mitigation actions such as Quantum key refresh, traffic rerouting, or attacker isolation are triggered and Performance evaluation of the system is based on Latency and throughput Experimental validation using Mininet and Ryu demonstrates secure key distribution, attack detection, and slice-specific threat mitigation. This integrated approach enhances end-to-end security for next-generation networks, with strong applicability to5G/6G, IoT, and mission-critical services.