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.
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.
The advent of quantum computing introduces fundamental challenges to contemporary cybersecurity, particularly by undermining the security assumptions of widely deployed cryptographic schemes. In parallel, the increasing sophistication, stealth, and adaptability of modern cyber threats expose the limitations of traditional, reactive security monitoring approaches. These developments motivate a shift toward defense strategies that are both quantum-resilient and intelligence-driven. This paper presents a comprehensive review of the convergence between post-quantum cryptography (PQC) and AI-driven threat hunting, focusing on the design and evolution of quantum-resilient defense frameworks. Rather than emphasizing empirical performance comparisons or speculative quantitative claims, the review adopts a concept-centric and analytically grounded perspective. It examines the foundational principles of post-quantum cryptography, the role of artificial intelligence in proactive threat hunting, and the emerging need to integrate cryptographic assurance with adaptive, learning-based security mechanisms. Existing architectural models, trust and risk abstractions, and formal security properties are analyzed to highlight how AI techniques can complement PQC by enabling continuous threat inference, contextual awareness, and adaptive response in post-quantum environments. The paper further synthesizes current research into a unified conceptual framework that captures the interaction between quantum-resistant cryptographic primitives and AI-based threat hunting processes. Key research gaps and open challenges are identified, including issues related to scalability, explainability, validation under future threat models, and the co-evolution of cryptographic and intelligent defense mechanisms. By consolidating fragmented research directions into a coherent analytical narrative, this review aims to serve as a foundational reference for future work on integrated, quantum-resilient cybersecurity architectures.
The advent of quantum computing has precipitated an estimated attack resistant cryptography system necessitating quantum attacks. The classical asymmetric algorithms, i.e., RSA and ECC are susceptible to Shor algorithm and a transition should be made to Post-Quantum Cryptography (PQC) anymore. The novelty of this work lies in providing a unified comparative framework that analyzes PQC families through security assumptions, concrete key/ciphertext sizes, and implementation complexity an aspect not addressed collectively in prior surveys. This survey gives a general picture of the status of the design process and general evaluation of PQC accounting its application within the paradigm of the diversified networks including the IoT and 5G/6G and in the cyber-physical environment. Furthermore, this review uniquely synthesizes practical hybrid‑deployment strategies, including protocol layering, coexistence models, and backward‑compatibility mechanisms, offering actionable guidance for real‑world migration. Additionally, the manuscript contributes a prioritized list of open problems across IoT, 5G/6G, blockchain, and cyber‑physical systems, highlighting domains facing the most urgent quantum‑resilience challenges. In this paper, the authors will evaluate the most popular PQC schemes, including schemes based on lattice, code, hash, and isogeny, depending on their performance, scalability, and interoperability (with reference to the recent research). It also examines the problems of integration as implemented with respect to the computational overhead, latency and adoption of hybrid with classical cryptography. This is expounded more to the standardization of PQC by NISTs and with a focus on such algorithms as CRYSTALS-Kyber and Dilithium. The findings suggest that, hybrid PQC protocols are able to control quantum resistance and actual performance in numerous infrastructures in computing systems.
The integration of artificial intelligence (AI) and machine learning (ML) into critical infrastructure has raised urgent concerns about data and model security, particularly in light of emerging quantum computing capabilities. Quantum algorithms threaten to render classical cryptographic methods obsolete, exposing AI/ML systems to potential breaches in confidentiality, integrity, and availability. This paper investigates the implications of quantum computing for securing AI/ML data both in transit and at rest and explores the development of quantum-safe networking protocols and cryptographic techniques. I examine post-quantum cryptographic (PQC) solutions including lattice-based, code-based, and hash-based algorithms, alongside the role of quantum key distribution (QKD) and AI-enhanced security orchestration. The study further addresses secure edge intelligence, federated AI systems, and emerging standards for 6G and beyond. My findings highlight both the necessity and complexity of transitioning to quantum-resilient infrastructure. Key challenges include computational overhead, legacy interoperability, and ethical concerns around AI-powered surveillance in quantum-secured environments. The paper concludes by emphasizing the need for proactive policy, investment in quantum-safe R&D, and cross-sector collaboration to safeguard AI/ML infrastructure in the post-quantum era.
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 development of quantum computers will provide modern cryptographic systems with a practical computing infrastructure, yet the number-theoretic assumptions these systems are built on poses an acute security risk at this juncture, especially when Shor and Grover’s algorithms are considered. In this article, we present QRC-Stack (Quantum Resilient Cryptographic Stack): A modular architecture for post quantum about cyber resilient communication in current and next generation infrastructures of the internet. QRC-Stack combines lattice-based and hash-based schemes with transport layers and key management to guarantee data integrity, confidentiality, and authenticity within classical networks as well as software-defined networks. The architecture of QRC-Stack is enhanced by incorporating hybrid key exchange models that integrate classical (e.g., ECDH) and post-quantum (PQ) cryptography; Kyber and Dilithium from NIST PQC finalists to sustain legacy interoperability while advancing resilience to future threats in quantum networked environments The newly proposed QRC-Stack model includes three interrelated parts that together improve the security and flexibility of cryptographic communication within a quantum-threat context. Starting with the key management layer for quantum-aware systems (QKML), it incorporates a session key distribution system that the quantum cryptography foe cannot breach. Furthermore, the Adaptive Cipher Suite Negotiation (ACSN) injects a more node centric, risk-adaptive model in whereby selection of a cryptographic suite from a pool of available options is done dynamically where the suit best optimizes contextual threat. In addition, Q-Protect Transport Module enables seamless alignment with pre-existing transport protocols such as TLS/IPSec and QUIC or SD-WAN tunnels with limited overhead footprint. Emulation testing on SDN testbeds and active WAN environments showed that QRC-Stack sustained enterprise-class encryption throughput while adding latency overhead less than eight percent. Moreover, this hybrid architecture gives forward secrecy and stronger resistance to quantum-enhanced man-in-the-mid solar attacks with faster key refresh rates. QRC-Stack also outperformed classical TLS 1.3 alongside other variants of Transition Post Quantum Cryptography’, claiming steadfast post-compromised security while surpassing baseline models in adaptability, resilience, and versatility making it ideal for next-generation network backbone design. This information reconfirms QRC-Stack's supurb strength as an extensible multi layered blanced framework solution for communication systems in layers form situated in scenarios involving surveillance from powerful post-quantum adversaries. It helps to control the move toward safely moving quantum national, enterprise, and IoT networks from cryptographic systems built for surveillance heavy environments with minimal changes to current infrastructure.
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.