The novel 6G-communication systems offer unparalleled opportunities in terms of reliability, speed and intelligence of the communication path. However, the characteristics of 6G network include dynamic nature and various type of nodes which make scenario more complex and open to various types of security threats such as advanced attacker and quantum attacker. As a result, this paper introduces an Adaptive Covert Communication Framework that combines quantum cryptography, and artificial intelligent-based physical layer security, and covert communication methods for secure and undetectable signal transmission. It uses the BB84 protocol for quantum key distribution and realizes the secure key rate up to 784 kbps over 10 km of quantum channel with 2 percent photon loss per kilometer. The AI models are used in real-time threat monitoring coupled with real-time reconfiguring in case of an adversarial situation, hence ensuring the detection probability of 5% during adversarial movements. Additional measures are added into the communication paradigm to ensure that the probability of interception is significantly reduced while offering a very high data rate of 1.2Gbps through frequency-hopping spread spectrum (FHSS) and signal obfuscation. The system also ensures energy efficiency with energy consumption of only 0.1 J/bit and thus has the possibility of being applied in different 6G applications. The analysis of different types of attacks demonstrates that the framework remains stable under different types of attacks such as jamming attack and quantum eavesdropping attack. The results show that the proposed framework can fit the current and future 6G security requirements to deliver efficient end-to-end protection in next-generation networks.
The novel 6G-communication systems offer unparalleled opportunities in terms of reliability, speed and intelligence of the communication path. However, the characteristics of 6G network include dynamic nature and various type of nodes which make scenario more complex and open to various types of security threats such as advanced attacker and quantum attacker. As a result, this paper introduces an Adaptive Covert Communication Framework that combines quantum cryptography, and artificial intelligent-based physical layer security, and covert communication methods for secure and undetectable signal transmission. It uses the BB84 protocol for quantum key distribution and realizes the secure key rate up to 784 kbps over 10 km of quantum channel with 2 percent photon loss per kilometer. The AI models are used in real-time threat monitoring coupled with real-time reconfiguring in case of an adversarial situation, hence ensuring the detection probability of 5% during adversarial movements. Additional measures are added into the communication paradigm to ensure that the probability of interception is significantly reduced while offering a very high data rate of 1.2Gbps through frequency-hopping spread spectrum (FHSS) and signal obfuscation. The system also ensures energy efficiency with energy consumption of only 0.1 J/bit and thus has the possibility of being applied in different 6G applications. The analysis of different types of attacks demonstrates that the framework remains stable under different types of attacks such as jamming attack and quantum eavesdropping attack. The results show that the proposed framework can fit the current and future 6G security requirements to deliver efficient end-to-end protection in next-generation networks.
Improved security against cyber-attacks, eavesdropping, and interference threats is necessary to establish 6G networks. With its inherent spatial confinement and high-rate data transmission, Visible Light Communication (VLC) can substitute conventional radio frequency (RF)-based security techniques challenged by spectrum congestion and jamming attacks. Constraints such as eavesdropping threats, low flexibility to mobility constraints, and time-varying environmental interference are issues that face VLC security solutions. Adaptive Quantum-Secured Visible Light Communication (AQ-SVLC) has been proposed to mitigate these issues. The paradigm combines Quantum Key Distribution (QKD), artificial intelligence-based adaptive beamforming, real-time channel state monitoring, and blockchain-based authentication with the aim of enhancing trustworthiness, flexibility, and confidentiality. The AQ-SVLC design guarantees real-time security adaptation by dynamically adjusting transmission parameters using Deep Reinforcement Learning (DRL) models. A hybrid optical-RF switching mechanism allows flawless connectivity even when the lighting changes. In 6G networks, the results show that AQ-SVLC provides a future-proof and scalable solution for strong physical layer security, far better than traditional VLC security techniques. For the purpose of guaranteeing that next-generation wireless communication ecosystems have security that is both adaptive and supported by AI, this research presents AQ-SVLC as a revolutionary method. While reducing bit error rate (10.8%) and latency (32.8 ms), the suggested AQ-SVLC method outperforms current security solutions in secrecy (97.3%), robustness (99.8%), and efficiency (98.3%).
The object of research: Security architecture of heterogeneous 6G communication networks integrating terrestrial-aerial-space, characterized by intensive use of network function virtualization and software-defined technologies. Investigated problem: The investigated problem concerns the significant expansion of the attack surface in 6G networks caused by architectural heterogeneity, virtualization, and the emergence of large-scale quantum computing. Classical cryptographic and security mechanisms employed in previous generations of communication networks are no longer sufficient to counter advanced threats, including quantum-enabled attacks and the “Save Now, Decrypt Later” (SNDL) paradigm. The main scientific results: The research proposes an intelligent multi-layer security framework for 6G networks based on the synergistic integration of post-quantum cryptography (PQC) and artificial intelligence technologies. PQC mechanisms ensure long-term confidentiality and integrity of transmitted data in the presence of quantum adversaries, while artificial intelligence–driven modules enable proactive anomaly detection, behavioral analysis, and adaptive security management. The research substantiates the feasibility of creating an autonomous, self-learning, quantum-resistant security framework capable of dynamically responding to evolving cyber threats in strategic 6G telecommunication systems. The area of practical use of the research results: The research results can be applied to the design and deployment of secure 6G communication infrastructures, including critical telecommunication systems, virtualized network environments, satellite–terrestrial integrated networks, and future smart and mission-critical services. Innovative technological product: The innovative technological product presented in this research is an intelligent multi-layer quantum-secure security framework that combines post-quantum cryptographic primitives with artificial intelligence–based security orchestration and analytics. Scope of the innovative technological product: The proposed framework is universal in scope and can be adapted to a wide range of 6G use cases, including ultra-reliable low-latency communications, massive machine-type communications, integrated terrestrial–aerial–space networks, and critical infrastructure protection
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.
This paper explores the integration of Quantum Communication Networks (QCNs), semantic communication, and covert communication within the context of 6G and future wireless networks. Introducing a new Quantum Semantic Communications (QSC) framework that capitalizes on advancements in quantum machine learning and semantic representations, this framework dramatically enhances resource efficiency in QCN s. It does so by embedding only relevant classical data into compact, high-dimensional quantum states for transmission, achieving a potential resource reduction of 50-75% while boosting quantum semantic fidelity. The paper further examines Artificial Intelligence's (AI) transformative role in upgrading tra-ditional communication paradigms into more efficient semantic communication systems, utilizing deep learning and end-to-end methodologies to ensure precise conveyance and interpretation of meanings in transmitted information. Additionally, it explores incorporating covert communication strategies within systems supported by a Reconfigurable Intelligent Surface (STAR-RIS) and Non-Orthogonal Multiple Access (NOMA), emphasizing the enhanced security and stealth necessary for modern networks. By merging these sophisticated communication strategies, the paper anticipates a new era of telecommunications that significantly surpasses existing security, efficiency, and semantic accuracy capabilities, marking a progressive step towards future networks optimized for secure, efficient, and meaning-focused communication in the quantum and AI era.
This study explores the incorporation of Quantum Cryptography (QC) as a secure communication platform of Next-Generation Communication Networks (NGCNs) including 5G, 6G, and IoT-based networks. The study is dedicated to the BB84 Quantum Key Distribution (QKD) protocol, the main emphasis of which is the possibility to guarantee the confidentiality of the data and the detection of the eavesdropping by the presence of quantum states disturbances. A conceptual and analytical approach was used with theoretical modelling, algorithmic representation, and analytical analysis as a result of some fundamental parameters including Quantum Bit Error Rate (QBER), Key Generation Rate (KGR), and Secure Key Rate (SKR). The results indicate that quantum cryptography provides significant quantum cryptography in terms of key exchange efficiency, reduction in latency and resistance to quantum attacks over classical cryptographic systems. The findings also demonstrate that keeping QBER below 5 % is critical to have the best stability in the system and secure key-generation with network size up to 32 nodes at a latency of less than 15 ms. In general, the paper establishes that quantum cryptography is a physics-based security system of the future that offers secure transmission of sensitive data exchanges in future high-speed communication systems.
The advent of next-generation networks, epitomized by Sixth-Generation (6G) wireless systems, signifies a paradigm shift from the simplistic goal of connectivity to a complex ecosystem defined by the convergence of the physical, digital, and biological worlds. This transition, characterized by hyper-density, extreme heterogeneity, and the integration of novel paradigms like terahertz (THz) communications, reconfigurable intelligent surfaces (RIS), and non-terrestrial networks (NTN), fundamentally invalidates many of the security assumptions of previous generations. The very characteristics that enable unprecedented data rates, ultra-low latency, and massive machine-type communications—such as massive Multiple-Input Multiple-Output (MIMO), distributed ledger technologies, and artificial intelligence (AI)-driven network slicing—also expand the attack surface, introducing novel vulnerabilities ranging from intelligent jamming and eavesdropping in the physical layer to sophisticated adversarial attacks on AI-based network management functions. This article provides a comprehensive exploration of secure transmission techniques designed for this nascent landscape. It moves beyond the traditional paradigm of cryptography-as-an-overlay to advocate for a holistic, interdisciplinary approach where security is embedded as a foundational property across all protocol layers. The discussion commences with a critical re-evaluation of the evolving threat landscape, identifying key vulnerabilities unique to next-generation architectures. Subsequently, it delves into advanced physical layer security (PLS) techniques, demonstrating how the intrinsic randomness of the wireless channel can be leveraged for secret key generation and covert communications, particularly in the context of massive MIMO and THz bands. The narrative then transitions to the cryptographic layer, examining the imperative shift towards post-quantum cryptography (PQC) to counter the looming threat of quantum decryption, alongside the role of blockchain and distributed ledgers in establishing decentralized trust in a network devoid of fixed infrastructure. A significant portion of the article is dedicated to AI-native security, exploring both the potential of AI to create autonomous, self-healing security mechanisms and the critical vulnerabilities introduced by adversarial machine learning. The analysis culminates in an examination of securing the network’s foundational pillars, including the integrity of network slicing, the resilience of the Radio Access Network (RAN), and the security of non-terrestrial components. This article concludes that the security of next-generation networks is not merely a technical challenge but a foundational requirement for the socio-economic viability of a hyper-connected future, necessitating a continuous, adaptive, and unified security architecture that evolves in lockstep with the network itself.