The advent of 6G wireless communication promises improvements in signal coverage, data rates, and latency, addressing increased connectivity demands due to the proliferation of 5G, IoT, and augmented reality. This paper introduces a Quantum-Secured IoT Communication Framework designed for 6G Cognitive Radio Networks (CRNs) in order to cater to the growing need for dependable and protected connectivity. Noteworthy aspects of this framework encompass dual-layer authentication utilizing Quantum Key Distribution (QKD) and Public Key Infrastructure (PKI), secured spectrum access regulations, and efficient beamforming strategies. Moreover, the framework employs a Reinforcement Learning-based Ensemble Regression (RL-ER) model for spectrum sensing and a Multi-Layer Perceptron with Kalman Filter (MLP-KF) for Channel State Information (CSI) prediction. Simulations demonstrate that the framework significantly improves prediction accuracy, encryption and decryption times, and error rates, thereby enhancing IoT network performance with better signal coverage, reduced latency, and robust security.
The advent of 6G wireless communication promises improvements in signal coverage, data rates, and latency, addressing increased connectivity demands due to the proliferation of 5G, IoT, and augmented reality. This paper introduces a Quantum-Secured IoT Communication Framework designed for 6G Cognitive Radio Networks (CRNs) in order to cater to the growing need for dependable and protected connectivity. Noteworthy aspects of this framework encompass dual-layer authentication utilizing Quantum Key Distribution (QKD) and Public Key Infrastructure (PKI), secured spectrum access regulations, and efficient beamforming strategies. Moreover, the framework employs a Reinforcement Learning-based Ensemble Regression (RL-ER) model for spectrum sensing and a Multi-Layer Perceptron with Kalman Filter (MLP-KF) for Channel State Information (CSI) prediction. Simulations demonstrate that the framework significantly improves prediction accuracy, encryption and decryption times, and error rates, thereby enhancing IoT network performance with better signal coverage, reduced latency, and robust security.
The convergence of Sixth-Generation (6G) wireless networks and the Internet of Things (IoT) demands unprecedented levels of performance, scalability, and security. Traditional architectures are increasingly inadequate in addressing the computational and security challenges posed by massive IoT connectivity, ultra-low latency, and high data throughput. This paper proposes a novel quantum-assisted architecture that integrates quantum computing and quantum communication principles to enhance the efficiency and security of 6G-enabled IoT systems. The framework leverages quantum key distribution (QKD), quantum machine learning (QML), and entanglement-assisted routing to provide end-to-end encryption, intelligent resource allocation, and resilient data transmission. Our simulation results and comparative analysis demonstrate significant improvements in network throughput, latency, and security resilience compared to classical 6G-IoT architectures. This research establishes a foundational step toward realising secure and intelligent next-generation wireless networks through the integration of quantum technology.
As we move toward the rollout of 6G networks, we're stepping into an era of groundbreaking technological advancements. These next-generation networks promise ultra-low latency and seamless integration with artificial intelligence (AI) and the Internet of Things (IoT), unlocking a new level of connectivity and performance. However, with these powerful capabilities come significant security challenges. Traditional encryption methods may not be enough to protect the complex and highly sensitive data traveling through 6G networks. One of the most promising solutions lies in Quantum Communication, particularly Quantum Key Distribution (QKD)-a method that leverages the laws of quantum mechanics to enable highly secure encryption. This paper explores the emerging security risks in both terrestrial and satellite communication channels and reviews current research on integrating quantum communication into 6G infrastructure. Special attention is given to its potential within the metaverse, a rapidly evolving digital environment that demands robust and future-proof security frameworks. Key areas of focus include-Addressing security vulnerabilities in quantum communication, Enhancing infrastructure to support quantum technologies, Reducing error rates in quantum protocols. the paper aims to propose a flexible, forward-looking framework designed to ensure fast, secure communication for critical sectors such as finance, defense, and healthcare.
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.
Amidst the development of communication technologies, the limitations of 5G communication systems, particularly in security and resource management, have become increasingly apparent. As the 6G era approaches, there are growing demands for integrated systems that ensure robust security and optimize resource utilization. To address these challenges, this paper proposes a novel architecture that integrates classical communication channels and quantum key distribution (QKD) channels using wavelength-division multiplexing (WDM). This innovative approach allows classical and quantum channels to coexist within a single optical fiber, improving security and fiber utilization while reducing system complexity and cost. A key contribution of this work is introducing an AI-based prediction and management module, dynamically adjusting the quantum key generation rate according to real-time usage and forecasted demand. By leveraging machine learning, the module predicts quantum key consumption patterns, ensuring that the key generation rate aligns with the system’s security and performance requirements. This approach balances key generation and usage, minimizing resource waste and enhancing the system’s overall efficiency. The feasibility of the proposed architecture is validated through an analysis of spontaneous Raman scattering (SpRS), showing the architecture maintains high key generation rates and low quantum bit error rates (QBER) under optimal system conditions. Furthermore, an analysis reveals that the AI module meets the requirement of predicting key usage and managing the key generation rate. Lastly, the feasibility is further validated by an experiment. Overall, this study presents a comprehensive framework for integrating classical and quantum channels in future 6G networks, providing enhanced security, efficiency, and scalability.
As sixth-generation (6G) wireless networks come into existence, there is more ever-growing demand for high-speed and secure communication than ever before. Conventional cryptographic methods are facing growing constraints to keep pace with the challenging reality of cyberattacks. Quantum-based communication technologies like quantum key distribution (QKD), quantum encryption, and quantum-resistant protocols provide an inherently secure means of transmitting data. This study examines how quantum communication technologies can be embedded within 6G architectures to provide enhanced data protection. With the help of AI and machine learning, 6G networks are able to anticipate threats and counter them, and quantum technologies offer unbreakable physical-layer encryption. Proposed work examines the security, architectural requirements, and implementation practicalities of this integration. In addition, we discussed the potential effect of quantum computing on present cryptographic techniques and describe future research directions for deployment at scale of quantum-secure communication in next-generation wireless systems.
The relationship between quantum computing and the Internet of Things (IoT) is becoming a powerful pathway to develop secure, intelligent and sustainable network systems – however, present-day IoT architectures experience scalability challenges, as well as energy and data vulnerability, due to classical models in cryptography. This paper presents a Next Generation Quantum-IoT Communication Framework (QIoT-CF) that addresses these issues with quantum-based encryption, entanglement-assisted routing, and dynamic sustainability optimization for communication in the framework. The architecture uses Quantum Key Distribution (QKD) to ensure quality data security that is unbreakable, and it uses reinforcement learning–based queuing to balance energy consumption and communication reliability with heterogeneous IoT nodes. The simulations suggest that latency decreased by 45%, energy consumption improved by 43%, and the quantum bit error rate (QBER) improved by 52% relative to current IoT systems. The sustainability controller will change transmission policies based on carbon-aware energy metrics providing an acceptable trade-off between quantum performance and sustainability at-scale. The framework represents a critically significant advancement toward eco-intelligent quantum communication security situated within the 6G vision and beyond.