Smart cities necessitate ultra-secure and scalable communication frameworks to manage billions of interconnected IoT devices, particularly in the face of the emerging quantum computing threats. This paper proposes the QESIF, a novel Quantum-Enhanced Secure IoT Framework that integrates Quantum Key Distribution (QKD) with classical IoT infrastructures via a hybrid protocol stack and a quantum-aware intrusion detection system (Q-IDS). The QESIF achieves high resilience against eavesdropping by monitoring quantum bit error rate (QBER) and leveraging entropy-weighted key generation. The simulation results, conducted using datasets TON IoT, Edge-IIoTset, and Bot-IoT, demonstrate the effectiveness of the QESIF. The framework records an average QBER of 0.0103 under clean channels and discards over 95% of the compromised keys in adversarial settings. It achieves Attack Detection Rates (ADRs) of 98.1%, 98.7%, and 98.3% across the three datasets, outperforming the baselines by 4–9%. Moreover, the QESIF delivers the lowest average latency of 20.3 ms and the highest throughput of 868 kbit/s in clean scenarios while maintaining energy efficiency with 13.4 mJ per session.
Smart cities necessitate ultra-secure and scalable communication frameworks to manage billions of interconnected IoT devices, particularly in the face of the emerging quantum computing threats. This paper proposes the QESIF, a novel Quantum-Enhanced Secure IoT Framework that integrates Quantum Key Distribution (QKD) with classical IoT infrastructures via a hybrid protocol stack and a quantum-aware intrusion detection system (Q-IDS). The QESIF achieves high resilience against eavesdropping by monitoring quantum bit error rate (QBER) and leveraging entropy-weighted key generation. The simulation results, conducted using datasets TON IoT, Edge-IIoTset, and Bot-IoT, demonstrate the effectiveness of the QESIF. The framework records an average QBER of 0.0103 under clean channels and discards over 95% of the compromised keys in adversarial settings. It achieves Attack Detection Rates (ADRs) of 98.1%, 98.7%, and 98.3% across the three datasets, outperforming the baselines by 4–9%. Moreover, the QESIF delivers the lowest average latency of 20.3 ms and the highest throughput of 868 kbit/s in clean scenarios while maintaining energy efficiency with 13.4 mJ per session.
The evolution of smart cities will contribute to an increase in the use of interconnected physical/digital ecosystems, and consequently, an increase in threat surface for the cyber threats against the protected data streams. With the emergence of quantum-based cyberthreats, this has increased the potential range of types of cyber-attacks on protected data and increased the use of quantum-based means of conducting cyber-attacks on protected data. This research proposal presents an Internet of Things (IoT) smart city framework founded on quantum-secure standards that were developed for next-generation IoT smart cities. The IoT Smart City Framework is comprised of four levels of architecture: a Quantum Backbone, a Key Management Level, an Edge Gateway Level, and an IoT Device Layer. Consequently, through the use of this architecture, the IoT Smart City Framework can protect the IoT Smart City Network from future cybercriminal attacks while providing assurance that the IoT Smart City Framework has been 'future-proofed.' By utilizing strategically deployed quantum nodes, the proposed solution performs QKD and frees devices with limited resources from needing to perform highly computationally intensive cryptography in order to secure encrypted communications, instead employing Lightweight Encryption Standards in conjunction with Symmetric Keys established via QKD. Using simulated quantum channels and urban IoT workloads, our experimental results yield secret key rates between 12 and 18 kilobits/sec (kbps) with a low quantum bit error rate (QBER) of 1.8% to 3.2%. Based on these experimental results, we conclude that the proposed hierarchical security architecture provides a resilient security framework for urban essential services, with negligible energy consumption.
With the growing Internet of Things (IoT), many applications like traffic management, smart cities, environment monitoring, industrial automation and healthcare have been revolutionized. As the number of resourcelimited IoT devices grows and connects with each other, security issues have become more intricate and severe, such as unauthorized access, data tampering, replay attacks, and the rise in threat from quantum computing to traditional cryptographic methods. To solve those problems, this paper proposes Quantum Shield-IoT, which is a quantum-resilient hybrid security framework that combines the Quantum Key Distribution (QKD) protocol of BB84 with ASCON lightweight authenticated encryption, blockchain security, and cloud computing to ensure secure end-to-end data transmission in IoT. The BB84 protocol works both to generate quantum secure cryptographic keys, and to identify eavesdropping via Quantum Bit Error Rate (QBER) analysis. The generated keys are used by ASCON-128 to ensure efficient data confidentiality, integrity and authentication with low computation load, which makes it suitable for resourceconstrained IoT devices. Encrypted data are securely stored in the cloud while the data integrity and traceability of the SHA-256 hash values are ensured by being stored on the blockchain, making them irretrievable. Encrypted data are stored securely in the cloud, while the data integrity and traceability of the hash value ensure irretrievable storage through the blockchain. The proposed framework was implemented using IBM Quantum Qiskit, ASCON-128, blockchain platforms and cloud storage. Experimental results show that quantum bit error rate (QBER) varies from 2.1% to 3.5% for typical communication and 24.8% for eavesdropping attempts, proving reliable QKD. ASCON encryption range was between 8.2 ms and 69.5 ms, and blockchain verification was less than 25 ms for 1,000 transactions with more than 99% of the integrity accuracy. Moreover, the framework achieved an attack detection rate higher than 97.9% in several cyberattacks and hence provided a scalable, light-weight and quantum resistant security solution for next generation IoT ecosystems.
The rapid expansion of Internet of Things (IoT) applications in sectors like smart cities, healthcare, and industrial automation has introduced serious security challenges due to limited device resources and growing threats from quantum computing. Traditional cryptographic techniques such as RSA and AES are increasingly inadequate, particularly against quantum attacks, and face limitations in scalability and efficiency in multi-node environments. To overcome these challenges, this paper proposes a lightweight and quantum-resilient security framework for IoT networks based on Multi-Node Quantum Key Distribution (QKD) integrated with Elliptic Curve Cryptography (ECC), termed MNQ-ECC. The proposed architecture enables secure key generation and exchange across multiple nodes and includes four security phases: pre-deployment, registration, login, and authentication. Here, performance evaluation is carried out using Qiskit simulators under varying network conditions and key performance metrics such as key generation rate, entropy, latency, and communication overhead are analysed. The results demonstrate that MNQ-ECC achieves 99.5% resistance to quantum attacks, improves key generation efficiency by 30%, and reduces encryption overhead by 20% compared to standard ECC. These findings confirm the framework's effectiveness in securing IoT networks with high scalability, low latency, and strong resilience against classical and quantum threats.
The coupling of quantum-metering methods with cryptographic key exchanges spells out a new security paradigm model to safeguard Internet of Things (IoT) networks against rapidly changing cyberspace threats. The given assessment explains a quantum-advanced scenario that is operationally feasible and serves as a platform for quantum key distribution (QKD) along with classical post-quantum algorithms to deliver end-to-end confidentiality, integrity, and authentication features to a wide range of IoT devices. The model, by the virtue of quantum entanglement and photon polarization used in the creation of tamper-evident communication links, is invulnerable to adversarial-aided eavesdropping and computational assault methods and further offers a hybrid encryption protocol that has been demonstrated to alleviate key generation and exchange latency trade-offs - simultaneously maintaining scalability and effectiveness in resource-constrained IoT node environments. The key compromise probability is significantly lowered in the experimental results, along with the keys' entropy levels, which were generated in the pure QKD space as opposed to classicalbased RSA and ECC methods. Also, the framework investigates lightweight quantum-safe authentication techniques that can be used to establish trust at the device level. The output points to the enhanced resistance to quantum and classical attackers that can make the solutions work in real-time application IoT environments such as smart healthcare, autonomous systems, and industrial automation. Overall, the quantum-enriched model of cryptographic key exchange is next-gen IoT ecosystem to be implemented subsequently.
Abstract The rapid expansion of Internet of Things (IoT) infrastructures has heightened their exposure to sophisticated adversaries, including those equipped with quantum capabilities. This work introduces a hybrid framework that integrates post-quantum cryptography (PQC), quantum key distribution (QKD), and quantum machine learning (QML) to deliver quantum-resilient anomaly detection. A novel PQC-IoT dataset is generated using real-time Raspberry Pi sensors, enriched with 30+ features spanning 12 traffic classes (9 attacks, 3 benign), and incorporating PQC-specific metadata such as encryption latency and ciphertext size. Security is enforced through Kyber-512 encryption and a BB84-based QKD channel, while anomaly detection is performed using a quantum support vector machine (qSVM). Experimental results show that qSVM consistently outperforms classical SVM and XGBoost by 4--7% in accuracy, precision, recall, and F1-score, achieving up to 97.6% accuracy with encryption overhead limited to 5--7%. The framework maintains a Quantum Bit Error Rate (QBER) below 11% under noise models, validating its robustness. To the best of our knowledge, this is the first reproducible benchmark that unifies PQC, QKD, and QML into a single pipeline, offering a practical pathway toward quantum-secure IoT anomaly detection.
The exponential growth of the Internet of Things (IoT) and its integration into critical infrastructures has elevated the need for robust and future-proof security mechanisms. Traditional cryptographic systems, while effective today, are increasingly vulnerable to advancements in quantum computing. This paper explores the integration of Quantum Key Distribution (QKD) as a novel security paradigm for next-generation IoT ecosystems. QKD leverages the principles of quantum mechanics to enable unconditionally secure key exchange, immune to computational attacks. We propose an architecture where QKD-enabled edge gateways and IoT nodes facilitate real-time secure communication through quantum-secured channels. The study analyzes the feasibility of implementing QKD in resource-constrained IoT environments and evaluates its performance in terms of key generation rate, latency, and energy consumption. Simulation results demonstrate that the proposed QKD-IoT framework significantly outperforms conventional encryption protocols in resisting both classical and quantum-based attacks, making it a viable foundation for building post-quantum resilient IoT infrastructures. The research also outlines the challenges related to scalability, hardware integration, and key management, and proposes solutions through hybrid QKD-classical cryptography models. This work paves the way for a quantum-secure IoT future, ensuring trust, privacy, and integrity in hyper-connected digital ecosystems.