The 6G networks and quantum computing are converging, and the security must be changed by a paradigm shift. Here, it is suggested that a new Hybrid Quantum-AI Encryption Offloading (HQAEO) framework should be developed to provide secure 6G. HQAEO is synergistic and combines Post-Quantum Cryptography (PQC), AI-based threat detection, and Mobile Edge Computing (MEC). A smart algorithm gives the best separation of encryption between user equipment and edge servers, which reduces a weighted cost of latency and energy. An AI model that runs on the edge can support dynamic and adaptive security too, whereas a quantumresistant key mechanism will provide secure key exchange. Simulations show that HQAEO causes 32.7 percent and 41.3 percent latency and energy savings over local PQC, and a 28 percent improvement in zero-day attacks coverage over static protocols.
The 6G networks and quantum computing are converging, and the security must be changed by a paradigm shift. Here, it is suggested that a new Hybrid Quantum-AI Encryption Offloading (HQAEO) framework should be developed to provide secure 6G. HQAEO is synergistic and combines Post-Quantum Cryptography (PQC), AI-based threat detection, and Mobile Edge Computing (MEC). A smart algorithm gives the best separation of encryption between user equipment and edge servers, which reduces a weighted cost of latency and energy. An AI model that runs on the edge can support dynamic and adaptive security too, whereas a quantumresistant key mechanism will provide secure key exchange. Simulations show that HQAEO causes 32.7 percent and 41.3 percent latency and energy savings over local PQC, and a 28 percent improvement in zero-day attacks coverage over static protocols.
The evolution of 6G networks necessitates robust authentication and key agreement (AKA) protocols to counter emerging security challenges, particularly the threat posed by quantum computing. Existing 5G-AKA protocols remain vulnerable to user tracking, replay attacks, and false base station impersonation, while Elliptic Curve Cryptography (ECC) and RSA-based key exchanges face imminent obsolescence due to quantum attacks. This study examines the vulnerabilities of 5G-AKA and explores hybrid post-quantum cryptography (PQC) as a transitional security solution for 6G networks. We evaluate NIST-standardized PQC algorithms, focusing on their computational overhead, key size efficiency, and adaptability to heterogeneous network environments, including IoT and ultra-low latency applications. A comparative analysis of hybrid cryptographic schemes demonstrates that lattice-based (Kyber, Dilithium), hash-based (SPHINCS+), and code-based (BIKE, Classic McEliece) PQC techniques provide varying trade-offs between security, efficiency, and deployment feasibility. Furthermore, we propose a quantum-resistant 6G-AKA framework, integrating hybrid PQC, AI-driven trust mechanisms, and decentralized authentication to ensure scalability and interoperability. Experimental benchmarks highlight potential performance constraints, including latency in PQC-based key exchange and resource limitations in edge computing. Addressing these challenges requires the optimization of lightweight PQC implementations, formal security validation, and global standardization efforts. Our findings provide a roadmap for the secure transition to 6G authentication protocols, ensuring resilience against both classical and quantum threats.
The sixth generation (6G) of wireless networks is expected to surpass the limitations of 5G by enabling terabit-level data rates, sub-millisecond latency, and ultra-dense connectivity through the integration of space-air-land-sea infrastructures and AI-driven autonomous management. However, such advancements pose new challenges in computational scalability and security against quantum-enabled threats. Quantum Artificial Intelligence (QAI), combining quantum computing principles with AI, offers exponential computational efficiency, enhanced model capacity, and resilient cryptographic solutions. This paper reviews QAI-based protocols for 6G across three domains: security, focusing on Quantum Key Distribution (QKD) and post-quantum cryptography; computing, including quantumenhanced edge intelligence and hybrid optimization; and data processing, with emphasis on terahertz (THz) channel modeling, holographic content, and real-time decision systems. The convergence of 6G and QAI is shown to mark a paradigm shift toward secure, scalable, and intelligent communication infrastructures of the future.
The rapid evolution of communication networks, driven by the expansion of heterogeneous environments such as 6G, Internet of Things (IoT), and edge computing, has exposed a critical research gap in the lack of unified frameworks that jointly address intelligent network control and quantum-resilient security. Existing networking protocols were originally designed under static configurations and classical security assumptions, making them increasingly inadequate for dynamic, large-scale, and intelligent infrastructures exposed to quantum-enabled threats. At the same time, the emergence of Quantum Computing (QC) introduces severe security risks, as widely used cryptographic mechanisms supporting protocols such as Transport Layer Security (TLS) and Internet Protocol Security (IPsec) become vulnerable to quantum attacks. This paper presents a structured survey based on a systematic classification of recent literature across AI-enabled networking, Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD), and protocol-level integration approaches. The review categorizes existing works into AI-driven network optimization, quantum-resilient security mechanisms, and hybrid AI–QRC architectural frameworks, enabling a unified comparison of design strategies and deployment models. Furthermore, this survey analyzes how Artificial Intelligence (AI) techniques enable autonomous network operations while Quantum-Resilient Cryptography (QRC) approaches provide post-quantum security guarantees, highlighting their complementary roles in next-generation network design. The study further synthesizes key findings for a tightly coupled AI–QRC co-design, which remains an open challenge due to mismatched assumptions in control latency, cryptographic overhead, and protocol adaptability. Additionally, this review emphasizes the need for integrated frameworks that combine intelligence and quantum security to develop adaptive, scalable, and resilient network protocols for the post-quantum era.
Trustworthiness, privacy and resilience are expected to be essential requirements of 6G on top of various other conventional performance requirements such as data rate and latency. Primary authentication is a key procedure for initiating secure communication between User Equipment (UE) and Home Network (HN) in 3rd Generation Partnership Project (3GPP). However, primary authentication mechanisms used in 5G are vulnerable against quantum machines, replay attacks, and rouge base-station. To protect against these threats, we propose beyond 5G and 6G primary authentication methods to adapt hybrid mechanisms which combines Post Quantum Cryptography (PQC) and existing asymmetric algorithm with Perfect Forward Secrecy (PFS) guarantee. We evaluate proposed methods using our in-house developed Simulator “WirelessPQCSim.” Our proposed Hybrid mechanisms provide enhanced security without additional CPU overhead with respect to exiting 5G system. We also achieved up to 6.7x speed-up for PQC-based methods with respect to 5G system and provide low latency which is one of the KPI for 6G system.
The Hybrid approach in Quantum Cryptography creates adaptable security model which provides the safest Communication in the emerging quantum era. The development of quantum computing raise questions about the long-term security. Traditional algorithms, such as RSA, ECC, and Diffie-Hellman, which is seemed computationally secure but it can be effectively solved by quantum algorithms such as Shor's and Grover's. This problem leads to the origination of two key trends in current studies, namely Post-Quantum Cryptography (PQC), designing mathematical approaches to encryption resistant to quantum attacks; Quantum Key Distribution (QKD) using the principles of quantum mechanics to assure security in communications. Accordingly, this research proposes a hybrid security framework including reliable data encryption and authentication using PQC, combined with the safe key- exchange method of QKD. The model is implemented in Python, Qiskit, and PQClean's Kyber and Dilithium algorithms to show how these two paradigms can cooperate toward quantum- resilient communication. To present the system performance, key exchange efficiency, computational overhead, and security strength have been considered. According to the results, this hybrid approach gives superior defense against quantum threats while maintaining practical effectiveness for real-world applications such as cloud security, 6G networks, and the Internet of Things.
With the advent of post-quantum cryptography (PQC) standards, it has become imperative for resourceconstrained devices (RCDs) in the Internet of Things (IoT) to adopt these quantum-resistant protocols. However, the high computational overhead and the large key sizes associated with PQC make direct deployment on such devices impractical. To address this challenge, we propose an edge computing-enabled PQC framework that leverages a physical-layer security (PLS)assisted offloading strategy, allowing devices to either offload intensive cryptographic tasks to a post-quantum edge server (PQES) or perform them locally. Furthermore, to ensure data confidentiality within the edge domain, our framework integrates two PLS techniques: offloading RCDs employ wiretap coding to secure data transmission, while non-offloading RCDs serve as friendly jammers by broadcasting artificial noise to disrupt potential eavesdroppers. Accordingly, we co-design the computation offloading and PLS strategy by jointly optimizing the device transmit power, PQES computation resource allocation, and offloading decisions to minimize overall latency under resource constraints. Numerical results demonstrate significant latency reductions compared to baseline schemes, confirming the scalability and efficiency of our approach for secure PQC operations in IoT networks.