The fast growth of the Internet of Things (IoT) has posed considerable problems regarding the security, scalability, and effective co-ordination of resources between interdependent devices. The conventional centralized solutions have failed to manage the active and decentralized nature of IoT environments. Blockchain technology also proposes a secure and decentralized model of data management, but it is based on classical cryptography methods that are susceptible to new attacks by quantum computers. The need to develop quantum-resistant security mechanisms is noted by the development of quantum algorithms by Peter Shor and Lov Grover. The present paper introduces a proposal of Adaptive Quantum Blockchain based on the Framework of Secure IoT Resource Coordination which combines quantum cryptography, blockchain technology, and adaptive optimization methods. The suggested system is based on quantum-secure encryption techniques to improve the protection of data, whereas blockchain provides decentralization and transparency. Moreover, adaptive algorithms allow allocating resources dynamically and effectively manage the IoT networks. The architecture will enhance security, scalability, and performance in complicated IoT settings. The suggested solution offers a solid solution to next generation intelligent and secure distributed systems.
The fast growth of the Internet of Things (IoT) has posed considerable problems regarding the security, scalability, and effective co-ordination of resources between interdependent devices. The conventional centralized solutions have failed to manage the active and decentralized nature of IoT environments. Blockchain technology also proposes a secure and decentralized model of data management, but it is based on classical cryptography methods that are susceptible to new attacks by quantum computers. The need to develop quantum-resistant security mechanisms is noted by the development of quantum algorithms by Peter Shor and Lov Grover. The present paper introduces a proposal of Adaptive Quantum Blockchain based on the Framework of Secure IoT Resource Coordination which combines quantum cryptography, blockchain technology, and adaptive optimization methods. The suggested system is based on quantum-secure encryption techniques to improve the protection of data, whereas blockchain provides decentralization and transparency. Moreover, adaptive algorithms allow allocating resources dynamically and effectively manage the IoT networks. The architecture will enhance security, scalability, and performance in complicated IoT settings. The suggested solution offers a solid solution to next generation intelligent and secure distributed systems.
The Internet of Things (IoT) is expanding swiftly, offering ease in everyday life. As the IoT systems produce enormous volumes of data, frequently encompassing private and confidential information, it is imperative to ensure their security. To ensure the security in IoT systems, we present a blockchain-enabled data encryption scheme utilizing quantum computing. This consensus mechanism eliminates the need for outside central service providers and encrypts data and accumulates converted cipher-text using consensus nodes acting as proxy service nodes. This approach alleviates the constraints associated with storing and sharing private encrypted information securely over a decentralized network. The suggested protocol possesses security attributes to counter replay attacks, side-channel attacks, Sybil attacks, and eavesdropping attacks, while mitigating tampering risks through targeted verification. Experimental results demonstrate an accuracy rate of 93.33%, with any discrepancies attributed to quantum device errors. The proposed protocol combines quantum encryption and blockchain-based security to create a scalable, decentralized, and resilient framework for securing IoT data sharing.
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.
The rapid proliferation of Internet of Things (IoT) devices presents critical cybersecurity challenges, as traditional cryptographic methods often fail to provide both robust security and operational efficiency in resource-constrained environments. This paper introduces Adaptive Quantum Cryptography (AQC), a novel framework designed to secure next-generation IoT networks against evolving classical and quantum-computing threats. The AQC framework synergistically integrates Quantum Key Distribution (QKD) for unbreakable key exchange, Quantum Random Number Generators (QRNGs) for high-entropy key generation, and Post-Quantum Cryptography (PQC) for quantum-resistant data encryption. A key feature of the system is its dynamic adaptation mechanism, which leverages artificial intelligence to intelligently select and adjust cryptographic protocols in real-time based on current network conditions, device computational capabilities, and identified threat levels. This ensures optimal security without imposing excessive overhead on IoT devices. Our comprehensive experimental evaluation demonstrates that the AQC framework significantly outperforms classical techniques, achieving a 70% improvement in key exchange efficiency, a 50% reduction in computational load, and a 95% resilience rate against quantum-based attacks. By providing forward secrecy and robust authentication, the proposed AQC framework offers a scalable, energy-efficient, and future-proof security solution, paving the way for resilient and trustworthy IoT ecosystems in the post-quantum era.
With billions of resource-constrained devices exchanging sensitive data over heterogeneous networks, the fast-growing expansion of the Internet of Things (IoT) has heightened the concerns of security. In this regard, classical blockchain, despite its promise, has two main disadvantages: it cannot scale properly under massive IoT traffic and it can be vulnerable to quantum adversaries. This work attempts to fill these gaps through an analytical and empirical review of thirty recent models using blockchain, post-quantum cryptography, and quantum-native approaches. Conducted under the PRISMA guidelines, this review systematically examines how its models perform with respect to common security metrics: delay, complexity, throughput, security efficiency, and packet delivery ratio. The findings of the study suggest that regular adaptive blockchains with dynamic block size optimization and lightweight hashing consistently achieve high throughput (>900 Tx/sec) and packet delivery ratios (>95%) in IoT environments making them the most feasible solution in near term. In contrast, post-quantum models, using hybrid encryption and an optimized SIKE provide significantly enhanced resilience (security efficiency in the range of 92% to 96%) while introducing computational overhead unsuited for low-power devices. The frameworks of quantum blockchain, utilizing QKD-based authentication and heap-driven key distribution, provide unsurpassed security efficiency (>95%) but stay largely constrained experimentally at this stage. The synthesis from the empirical study suggests a multi-layered approach, consisting of immediate implementations of lightweight adaptive models, mid-term enhancements through post-quantum cryptography optimization, and a long-term aim of deployment of full quantum blockchain architecture. Such insights would prove pivotal in IoT sectors with real-time requirements like health, smart grids, and industrial automation, where balancing scalability, efficiency, and quantum resilience is of utmost importance. Hence, the work provides an avenue for foundational mapping of advancement in quantum-secure IoT ecosystems.
The rapid spreading of Internet of Things (IoT) applications have been significant challenges in achieving secure, lightweight and scalable authentication particularly due to the arising threats of quantum threats. In order to solve these issues, this paper introduces the Dynamic Adaptive Post-Quantum Elliptic Blockchain (DAPQEB) protocol which combines Elliptic Curve Cryptography (ECC), Post-Quantum Cryptography (PQC) and blockchain technology to perform decentralized and tamper-proof authentication. The protocol makes use of hybrid key generation based on ECC and PQC secrets, further supported by Key Derivation Function (HKDF)-based derivation of sessions and blockchain-based attestation that is not revoked. An active adaptation scheme also contributes to resilience by modifying the cryptographic functions depending on device resources and threat intensity, tradeoffs between performance and security. Experimental simulations on simulation networks are performed using several network sizes with energy model parameters, latency and adaptive thresholds. These findings prove that DAPQEB is more effective than the existing methods in energy consumption, throughput, ratio of packet delivery, network lifetime and detection rate. Although its generation, encryption and decryption time are slightly higher, these are reasonable trade-offs with increased robustness and quantum resistance. Altogether, DAPQEB is a resource-optimized, scalable and secure authentication system that is been applied in energy-sensitive and large-scale IoT networks.
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.