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International Conference on Next-Gen Quantum and Advanced Computing: Algorithms, Security, and Beyond (NQComp)

A Quantum-Secured IoT Framework for Next Generation Smart City Networks

Kesavan S R, H. Anwar Basha, S. Sasikumar, Madhan Veeramani, P. K. Nagarajan, V M Senthilkumar

Published Mar 5, 2026• 0 citations
Publisher

Abstract

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.

DOI
10.1109/nqcomp68334.2026.11497703

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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.
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.
Currently and in the near future, Smart Cities are vital to enhance urban living, address resource challenges, optimize infrastructure, and harness technology for sustainability, efficiency, and improved quality of life in rapidly urbanizing environments. Owing to the high usage of networks, sensors, and connected devices, Smart Cities generate a massive amount of data. Therefore, Smart City security concerns encompass data privacy, IoT vulnerabilities, cyber threats, and urban infrastructure risks, requiring robust solutions to safeguard digital assets, citizens, and critical services. Some solutions include robust cybersecurity measures, data encryption, AI-driven threat detection, public-private partnerships, standardized security protocols, and community engagement to foster a resilient and secure smart city ecosystem. For example, Security Information and Event Management helps in real-time monitoring, threat detection, and incident response by aggregating and analyzing security data. In this paper, we propose a Hybrid Quantum Architecture for bolstering Smart City security that exploits Quantum Machine Learning and SIEM to provide security based on Quantum Artificial Intelligence and patterns/rules. The validity of the architecture was proven by conducting experiments and a comparison of the QML algorithms with a state-of-the-art AI algorithms. We also provide a proof of concept dashboard for the proposed architecture.
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 rely on high-density digital infrastructures that include Internet of Things (IoT) devices, Artificial Intelligence (AI), cloud computing, digital identity systems, and operational technology. Although these systems improve efficiency and sustainability, they also provide a large cyber-physical attack surface. The problem is exacerbated by the advent of quantum computing, as popular public-key ciphers like RSA and elliptic-curve cryptography can be broken using quantum algorithms such as Shor's algorithm (Shor, 1994; Mosca, 2018). Smart cities rely on long-term data confidentiality, certificate-based trust, and remote management of critical infrastructure. This presents a strategic cyber resilience challenge. This thesis examines the impact of quantum technology on smart cities' cyber resilience, as well as how quantum-safe mechanisms can be integrated into urban digital infrastructure. The updated proposal now includes a critical literature review, case reasoning by comparison, a threat and vulnerability matrix, and a simulated BB84 quantum key distribution demonstration. According to NIST (2024b, 2024c, 2024d) and Pirandola et al. (2020), this thesis supports post-quantum cryptography (PQC) NIST standards FIPS 203, FIPS 204, and FIPS 205 as a scalable software migration strategy and quantum key distribution (QKD) as a selective protection strategy for high-value fixed communication links. The analysis demonstrates that quantum-safe resilience cannot be achieved solely through one technology. Any practical smart city transition must include a cryptographic inventory, data lifetime assessment, risk-based prioritization of critical services, hybrid migration, continuous monitoring, and governance. According to the simulation, the quantum bit error rate increases during the intercept-resend attack, alerting Alice and Bob to the eavesdropping activity and allowing them to discard the common key. The proposed framework integrates post-quantum cryptography for a wide range of software and cloud services, quantum key distribution for specific critical infrastructure links, and NIST Cybersecurity Framework 2.0 governance functions to ensure ongoing operational resilience.
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 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.