Quantum communication networks have emerged as a promising solution for secure information exchange using quantum mechanical principles such as entanglement and quantum key distribution (QKD). However, most existing multi-user quantum communication frameworks rely on static protocol execution strategies that continuously perform reconciliation and verification procedures irrespective of real-time communication conditions. Such behaviour increases communication overhead, latency accumulation, and resource consumption under dynamically varying network environments. This paper proposes an adaptive QBERaware protocol orchestration framework for secure and scalable multi-user quantum communication networks. This work continuously monitors Quantum Bit Error Rate (QBER), channel noise, communication delay, and traffic density to dynamically regulate communication execution intensity according to network stability conditions. A lightweight threshold-driven orchestration mechanism is introduced to selectively activate communication and security procedures while preserving transmission integrity. Experimental evaluation demonstrates that this work reduces protocol overhead, improves scalability, minimizes communication latency, and enhances adaptive responsiveness when compared with conventional static execution approaches. This work architecture provides a computationally efficient and adaptive communication management framework suitable for next-generation distributed quantum networking infrastructures.
Quantum communication networks have emerged as a promising solution for secure information exchange using quantum mechanical principles such as entanglement and quantum key distribution (QKD). However, most existing multi-user quantum communication frameworks rely on static protocol execution strategies that continuously perform reconciliation and verification procedures irrespective of real-time communication conditions. Such behaviour increases communication overhead, latency accumulation, and resource consumption under dynamically varying network environments. This paper proposes an adaptive QBERaware protocol orchestration framework for secure and scalable multi-user quantum communication networks. This work continuously monitors Quantum Bit Error Rate (QBER), channel noise, communication delay, and traffic density to dynamically regulate communication execution intensity according to network stability conditions. A lightweight threshold-driven orchestration mechanism is introduced to selectively activate communication and security procedures while preserving transmission integrity. Experimental evaluation demonstrates that this work reduces protocol overhead, improves scalability, minimizes communication latency, and enhances adaptive responsiveness when compared with conventional static execution approaches. This work architecture provides a computationally efficient and adaptive communication management framework suitable for next-generation distributed quantum networking infrastructures.
Abstract Quantum networks provide both security and faster communication; however, they face critical challenges in terms of dynamic resource allocation and maintaining robust security. Current static allocation methodologies frequently lead to excessive latency and attack vulnerabilities, which restrict performance and scalability. To address these challenges, this article presents a secure and adaptive resource allocation outline for quantum networks, merging quantum-enhanced security protocols with real-time optimization. The framework utilizes Quantum Key Distribution - Single Center Method (QKD-SCM) to exchange secure and scalable keys. and the Stochastic Programming and the Cooperative-Qubit-Allocation-Problem (SP-CQAP), which addresses dynamic resource allocations. High-fidelity entangled resources are managed with the Fidelity Maintenance Scheme Based on Prioritized Purification (FMSPP), and congestion is avoided using Self-Adaptive and Content-Based Scheduling (CACS). The proposed framework was evaluated using NS-3.30.1 and Python 3.7.4, running on Ubuntu 18.4 LTS. In comparison to already-existing methodologies within the segment, the proposed framework demonstrated reduced latency of 20 ms, energy efficiencies of 90%, a quantum key distribution success rate of 90%, and resource utilization equating to 70%. The findings demonstrate the promise of quantum-enhanced wireless communication through dynamic resource allocation for safe, low-latency, and high-performance networking. Removed: security enhancement implied earlier.
The fast growth of Internet of Things (IoT) networks has heightened the demand for secure, scalable and energy efficient communications methods. Traditional cryptographic techniques are more susceptible to quantum computing attacks and therefore have pushed the necessity for quantum secure methods. This study presents an energy efficient artificial intelligence assisted quantum secure communication framework designed to scale and provide reliable IoT networks. The framework uses Quantum Key Distribution (QKD) combined with deep learning optimization to improve both relationship and network performance. A self-adaptive AI module applies its lower level of computational resources and dynamically changing network conditions in order to optimize key management, routing decisions, and resource allocation, which reduces both energy consumption and communication latency. The proposed system is intended to support the specific types of constraints faced within an IoT environment. The experimental simulation results demonstrate that the framework improves energy efficiency, increases packet delivery ratio, and decreases latency in IVN (Intelligent Vehicular Networks) by comparison with traditional means of secure communication. In addition, by combining AI and quantum communications, we increase our resilience to threats posed by both classical and quantum forms of attack while providing an added layer of protection for transmitting data between devices in future wireless networks. Additionally, this proposed framework will provide a very scalable and effective method for providing IoT solutions within the environment of 5G mobile networks or later generations.
The rapid expansion of the Internet of Things (IoT) has introduced unprecedented cybersecurity challenges, as traditional cryptographic methods struggle to provide both efficiency and quantum resistance in resource-constrained environments. This research introduces Adaptive Quantum Cryptography (AQC), a novel security framework that integrates Quantum Key Distribution (QKD), Post-Quantum Cryptography (PQC), Quantum Random Number Generators (QRNGs), and AI-driven dynamic adaptation to safeguard IoT networks against evolving cyber threats. Unlike classical encryption techniques such as RSA and ECC, which are vulnerable to quantum attacks, AQC leverages quantum mechanical principles—such as superposition, entanglement, and the no-cloning theorem—to ensure provably secure key exchange and data encryption. The proposed AQC system dynamically adjusts cryptographic protocols based on real-time network conditions, computational resources, and threat intelligence, optimizing security without imposing excessive overhead. Experimental evaluations demonstrate that AQC achieves a 70% improvement in key exchange efficiency, a 50% reduction in computational load, and a 95% resilience rate against quantum attacks compared to conventional encryption methods. Additionally, the integration of QRNGs enhances cryptographic key entropy, while AI-driven anomaly detection enables proactive threat mitigation. This framework is particularly suited for next-generation IoT applications, including smart grids, autonomous vehicles, and industrial automation, where security, scalability, and energy efficiency are critical. By combining quantum-resistant algorithms with adaptive security mechanisms, AQC provides forward secrecy, resistance to quantum adversaries, and robust authentication, ensuring long-term protection for IoT ecosystems in the post-quantum era. The findings underscore AQC’s potential as a foundational security architecture for future quantum-safe IoT networks.
Quantum Key Distribution (QKD) and encryption protocols are central to secure user-to-user communication in quantum networks. However, the detection of eavesdropping, security vulnerabilities, and performance degradation at high traffic levels are some of the challenges faced by inefficient multi-user communication. Current approaches do not adequately overcome these challenges. This paper suggests a holistic framework that integrates QKD, classical-quantum multiple access techniques, and advanced security protocols for overcoming these issues. This framework uses the QKD-SCM for communication security across several nodes and makes use of classical-quantum multiple accesses for greater speed and scalability in communication. Security is then further optimized with the MUQQ-ESTMP GHZ based on Multi-User Quantum Protocol, (MUQPQ), where it optimizes queries across several users. Lattice-based cryptography is deployed to protect against quantum computing attacks, and for detecting eavesdropper attacks, the Reverse Reconciliation Algorithm for binary-input additive white Gaussian noise channel (RRA-BIAWGNC) is used. Furthermore, QPQB has been integrated as a searchable symmetric encryption protocol to safeguard the data in cloud storage. The performance of the system has been analyzed with metrics like detection accuracy of eavesdrop attack (97%), communication complexity (95%), effective key rate (590 b/s), communication efficiency (96%), and computational overhead (98%). Simulation has been carried out using ns-3.30.1 and Python. Simulation results indicate a considerable reduction in communication complexity up to 40% and enhanced detection accuracy that surpassed the existing stateof- the-art benchmarks. Through the integration of multiple advanced techniques for security, this research contributes to the development of scalable and quantum communication networks with security.
The emergence of quantum computing threatens conventional cryptographic systems securing military communications. This paper proposes a quantum-resistant cryptographic framework specifically designed for military networks’ unique constraints. We evaluate post-quantum cryptographic algorithms across strategic, operational, and tactical communication tiers using a novel Dynamic Algorithm Switching Protocol that adapts algorithm selection based on mission requirements and available resources. Our multi-tiered approach implements lattice-based algorithms for tactical communications and hybrid classical/post-quantum systems for strategic networks. Simulations demonstrate that lattice-based algorithms reduce computational overhead by 12.6% and bandwidth consumption by 18.3% compared to alternatives, while hash-based mechanisms improve security margins by 24.7% with acceptable latency increases. Field tests confirm our framework maintains tactical communication latency under 15ms with only 8% reduction in effective range. The proposed adaptive framework successfully balances security and performance, achieving 92.7% optimal algorithm selection across varying network conditions—significantly outperforming static approaches. We conclude with a phased implementation strategy and recommendations for military adoption of quantum-resistant cryptography.
The development of large-scale quantum networks requires not only advances in physical-layer technologies but also a comprehensive protocol stack that integrates communication, control, and resource management across all layers. We present the first such protocol stack, which introduces a Global Entanglement Module (GEM) that maintains a consistent, network-wide view of entanglement resources through distributed synchronization strategies. By enabling real-time adaptive execution of entanglement distribution plans, GEM bridges the gap between static planning and dynamic operation. The stack naturally supports pre-distributed entanglement, purification, and multi-partite state generation, making it applicable to a broad range of quantum networking applications. We design and evaluate multiple adaptive heuristics for real-time execution and show that a lightweight scoring-based strategy consistently achieves the best performance, improving entanglement generation rates by about 20% over a globally optimal but non-adaptive fixed-tree baseline and achieving more than a two-fold improvement relative to recent connectionless approaches. Across all scenarios-including predistribution and fidelity analysis-GEM consistently enables lower latency and robust operation. These results establish a practical pathway toward scalable, adaptive quantum internet systems.