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International Journal of Engineering Trends and Technology

Enhanced Quantum Key Distribution Using Non-Symmetric Quantum Channels and Super Dense Coding With Cascade Splitting Neural Networks

Bosubabu Sambana, Kondapalli Venkata Ramana

Published Jul 31, 2025• 0 citations
Publisher

Abstract

Quantum Key Distribution (QKD) systems using quantum mechanical ideas offer a secure approach for the cryptographic key exchange. In contrast, rational implementations of QKD are prone to critical defects compromising their security in practical applications in the industry. Still, some main challenges remain: the public channel exposure for the ciphertext transmission, the insecure key transfer to communication terminals, and the exposure of keys in the Quantum Distribution Channel (QCh). Side-channel exploits, intercept-resend attacks, and photon number splitting (PNS), all of which reduce the general security and efficiency of key exchange, are vulnerabilities of current symmetric QKD systems. To achieve real-time threat detection, this work presents an enhanced QKD protocol using a non-symmetric quantum channel in combination with superdense coding and a cascade splitting neural network. The non-symmetric quantum channel minimizes the sensitivity of symmetric key attacks using controlled asymmetry in the main distribution mechanism. Entanglement lets super dense coding encode two bits of information for every qubit, so increasing transmission efficiency. The research follows the quantum channel and communication terminals using a cascade splitting neural network. This system is meant to find abnormalities and probably listen in on attempts. The neural network is constructed by several layers of cascading neurons, which enables real-time risk detection and flexible response to security breaches. Numerical results obtained from simulated quantum communication networks show that the proposed protocol achieves a 27% increase in key-generating rate and a 35% decrease in transmission error rate when compared to conventional symmetric QKD protocols. Moreover, the enhanced protocol ensures a safe and consistent key exchange when quantum communication is applied by raising the 31% accuracy of eavesdropping detection. QKD has improved in terms of both security and economy by using a non-symmetric quantum channel, super dense coding, and intelligent threat detection.

DOI
10.14445/22315381/ijett-v73i7p143

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Quantum Key Distribution (QKD) systems using quantum mechanical ideas offer a secure approach for the cryptographic key exchange. In contrast, rational implementations of QKD are prone to critical defects compromising their security in practical applications in the industry. Still, some main challenges remain: the public channel exposure for the ciphertext transmission, the insecure key transfer to communication terminals, and the exposure of keys in the Quantum Distribution Channel (QCh). Side-channel exploits, intercept-resend attacks, and photon number splitting (PNS), all of which reduce the general security and efficiency of key exchange, are vulnerabilities of current symmetric QKD systems. To achieve real-time threat detection, this work presents an enhanced QKD protocol using a non-symmetric quantum channel in combination with superdense coding and a cascade splitting neural network. The non-symmetric quantum channel minimizes the sensitivity of symmetric key attacks using controlled asymmetry in the main distribution mechanism. Entanglement lets super dense coding encode two bits of information for every qubit, so increasing transmission efficiency. The research follows the quantum channel and communication terminals using a cascade splitting neural network. This system is meant to find abnormalities and probably listen in on attempts. The neural network is constructed by several layers of cascading neurons, which enables real-time risk detection and flexible response to security breaches. Numerical results obtained from simulated quantum communication networks show that the proposed protocol achieves a 27% increase in key-generating rate and a 35% decrease in transmission error rate when compared to conventional symmetric QKD protocols. Moreover, the enhanced protocol ensures a safe and consistent key exchange when quantum communication is applied by raising the 31% accuracy of eavesdropping detection. QKD has improved in terms of both security and economy by using a non-symmetric quantum channel, super dense coding, and intelligent threat detection.
Quantum Key Distribution (QKD) promises theoretically unbreakable encryption by using fundamental quantum physics principles. QKD has emerged as a contender in the next generation of encryption protocols as the demand for more secure communication grows in our linked society. However, practical QKD implementations confront obstacles such as noise, interception attempts, and flaws in quantum hardware. We investigate the possibilities of Machine Learning (ML) techniques to improve the efficiency, resilience, and security of QKD protocols in this study. We provide a novel system that uses deep learning models to optimize photon polarization states and hence increase the key generation rate. Our approach detects and mitigates eavesdropping attempts using unsupervised learning algorithms, substantially enhancing the security of quantum communications. To achieve security, the BB84 protocol makes use of fundamental quantum mechanics features. Furthermore, we use reinforcement learning to adaptively alter system settings in real time to account for the quirks and noise profiles of different quantum channels. In comparison to typical QKD setups, experimental results show that our ML-enhanced QKD system is more resilient to known quantum attacks and provides a more consistent and efficient key distribution rate. Our findings indicate that the interaction of quantum physics and machine learning can pave the way for more secure and practical quantum communication networks in the near future.
The accelerating development of quantum computing capabilities poses an unprecedented challenge to conventional encryption methodologies that currently underpin global digital security infrastructure. Classical cryptographic systems, including widely adopted standards such as RSA and AES, derive their security from the computational intractability of specific mathematical problems, a foundation that quantum algorithms threaten to fundamentally undermine. This research presents a comprehensive investigation into the practical implementation of Quantum Key Distribution as a transformative approach to establishing unconditionally secure communication channels. Through experimental deployment of the BB84 protocol augmented with advanced quantum error correction and privacy amplification techniques, we systematically evaluate the performance characteristics and security guarantees of QKD in realistic network environments. Our experimental framework achieves a secure key generation rate of 2.5 megabits per second while maintaining an average quantum bit error rate of 3.2 percent, demonstrating the practical viability of quantum-secured communication. The implementation exhibits exceptional eavesdropping detection capabilities with a 98.5 percent success rate in identifying unauthorized interception attempts. Comparative security analysis reveals that QKD-based encryption reduces vulnerability to brute-force attacks by 65 percent when contrasted with classical encryption standards. The integration of lattice-based post-quantum cryptographic algorithms provides an additional security layer against store-now-decrypt-later attack strategies. These findings substantiate the position of Quantum Key Distribution as a cornerstone technology for next-generation cybersecurity frameworks, offering robust protection against both current threats and the anticipated capabilities of large-scale quantum computers.
Built based on the fundamental principles of quantum mechanics, Quantum Key Distribution (QKD) enables secure communication for distant parties. Entanglement-based protocols are a type of QKD protocol that uses the phenomenon of entanglement for detecting eavesdroppers between two communicating parties. In this paper, a novel QKD protocol is devised that uses the concept of superdense coding and padding bits to share the one-time pad, i.e., the key. The super dense coding is achieved by sharing a pre-existing entangled pair of qubits by leveraging the beautiful property of entanglement. The communicating parties can share a one-time pad using this protocol securely. This paper will demonstrate this phenomenon using the proposed protocol by showing the experimental results which has been surfaced with IBM Qiskit simulator, and the simulation establishes the applicability of the protocol and shows its effectiveness in detecting eavesdropping attempts while being simple to implement.
This paper proposes a novel quantum key distribution (QKD) protocol leveraging quantum entanglement for enhanced security and reduced key exchange latency. The protocol utilizes entangled photon pairs to generate a shared key, combined with quantum error correction codes for reliable key recovery. The core innovation lies in the efficient use of entanglement for key generation and transmission, offering a significant improvement over classical key exchange methods. The protocol's performance is analyzed, demonstrating its potential to bolster security against eavesdropping attacks and minimize the time required to establish a secure key. The design addresses key limitations of existing QKD protocols, particularly those related to distance and efficiency. Furthermore, the integration of quantum error correction directly contributes to a more robust and practical system. This research contributes to the ongoing advancements in quantum cryptography and represents a critical step towards secure quantum communication networks.
Traditional cryptographic methods are becoming more and more vulnerable when facing the computing power delivered by the quantum algorithm in the era of digitalization heading towards quantum computing. The realization of a quantum computer is a growing menace that has promoted the development of Quantum Key Distribution (QKD), a completely secure key exchange protocol based on the principles of quantum mechanics. This work studies QKD protocol creation and use for secure data transfer in hybrid networks including both classical and quantum computing nodes over geographically separated environments. The paper provides a scalable scheme to integrate QKD with current classical communication networks, with the emphasis on interoperability, key synchronization, secure routing among the mixed nodes. At the core of the model are quantum channels for key exchange and classical channels for data, governed by a quantum-safe control protocol. The security of QKD—the feature of resistance against eavesdropping according to the no-cloning theorem and disturbance of measurement—is investigated taking into account actual implementation aspects, such as noise, restriction in a transmission distance, and quantum memory. To test the model, simulation, and prototype testing are performed over different networking topologies, considering various parameters such as QBER, key generation rate, latency and system robustness under different attacks such as man-in-the-middle as well as photon-number-splitting attacks. We also investigate the interworking between QKD and post-quantum cryptography (PQC) to reduce the risk for hybrid systems with enhanced security and to be backward compatible to classical systems. Findings show that, when well combined with classical and quantum computing nodes, QKD is able to bring the cybersecurity of today communication infrastructures to a greater extent. This research is a step towards building the quantum internet, providing a solid foundation for applications in cybersecurity and potentially well beyond — finance, defense, health care and more — where data privacy truly matters.
The integration of Quantum Key Distribution (QKD) with Machine Learning (ML) has developed a high-end, secure model for accurate data transmission and network security. Many existing systems face several issues due to advances in quantum computing. Thus, integrating these models improved the efficiency, accuracy, and feasibility of QKD systems. In this paper, an Advanced Learning Approach (ALA) is combined with the Quantum Key Distribution Framework to refine key generation, error correction, and intrusion detection in quantum communication channels. The proposed ALA also used reinforcement learning algorithms to predict quantum channel fluctuations, dynamically adjust key exchange parameters, and strengthen authentication protocols. Simulation results demonstrate improved key rates, reduced Quantum Bit Error Rates (QBER), and enhanced resilience against eavesdropping attacks. The study contributes to the realization of practical, scalable, and intelligent quantum-secure communication systems—bridging the gap between theoretical quantum security and real-world network deployment.