This paper analyzes the performance of two quantum key distribution (QKD) protocols, SARG04 and BB84, under different random quantum noise levels. It also looks at the protocols’ potential applications in Internet of Things (IoT) device security for a proposed architecture. In the proposed model, long-range photons are inherently vulnerable to quantum noise, which complicates real-world QKD implementations and jeopardizes the reliability and resilience of the secret key generation process. By simulating different noise situations, we evaluate the overall security performance, mistake rates, and key generation rates of the BB84 and SARG04 protocols. Our findings suggest that although both protocols can withstand moderate noise levels, SARG04 and BB84 perform similarly regarding secure key length. We also address the consequences of these results for the security of the Internet of Things, highlighting QKD’s role in minimizing vulnerabilities related to conventional cryptography techniques. QKD integration can improve data security and privacy in Internet of Things frameworks, offering a viable way to protect sensitive data in increasingly networked devices. This work significantly contributes to the current efforts in quantum cryptography research by providing insightful advice on protocol selection and secure IoT connectivity implementation techniques.
This paper analyzes the performance of two quantum key distribution (QKD) protocols, SARG04 and BB84, under different random quantum noise levels. It also looks at the protocols’ potential applications in Internet of Things (IoT) device security for a proposed architecture. In the proposed model, long-range photons are inherently vulnerable to quantum noise, which complicates real-world QKD implementations and jeopardizes the reliability and resilience of the secret key generation process. By simulating different noise situations, we evaluate the overall security performance, mistake rates, and key generation rates of the BB84 and SARG04 protocols. Our findings suggest that although both protocols can withstand moderate noise levels, SARG04 and BB84 perform similarly regarding secure key length. We also address the consequences of these results for the security of the Internet of Things, highlighting QKD’s role in minimizing vulnerabilities related to conventional cryptography techniques. QKD integration can improve data security and privacy in Internet of Things frameworks, offering a viable way to protect sensitive data in increasingly networked devices. This work significantly contributes to the current efforts in quantum cryptography research by providing insightful advice on protocol selection and secure IoT connectivity implementation techniques.
The rapid proliferation of Internet of Things devices (IoT) across healthcare, smart homes, transportation, and industrial automation has led to an unprecedented exchange of sensitive data over wireless channels, exposing these networks to cyberattacks, eavesdropping, and unauthorized access.Conventional cryptographic techniques, which rely on computational hardness assumptions, are increasingly vulnerable to the emerging capabilities of quantum computing.This paper explores the application of Quantum Key Distribution (QKD) as a means of enabling secure and dependable data communication for IoT devices.By exploiting the fundamental principles of quantum mechanics, QKD allows two communicating parties to generate a shared secret key while inherently detecting any attempt at interception.The proposed approach aims to enhance data privacy, ensure secure authentication, preserve confidentiality, and safeguard IoT systems against present and future quantum enabled threats.The integration of quantum based security techniques into existing IoT infrastructure is examined, along with its implications for improving the reliability and trustworthiness of wireless IoT communication systems.This work positions Quantum Enhanced Secure Data Communication as a forward looking security solution for next generation IoT networks.
The Internet of Things (IoT) has experienced rapid growth, resulting in a proliferation of interconnected devices in domains such as smart homes, cities, and healthcare applications. Ensuring secure communication within IoT networks is crucial for protecting privacy and data. The BB84 protocol, a quantum key distribution (QKD) protocol, shows promise in enhancing IoT communication security. This paper presents a comprehensive security analysis of the BB84 protocol in IoT networks, examining key aspects including entropy, execution time, quantum bit error rate (QBER), and cryptographic key generation efficiency. The analysis aims to evaluate the protocol's resilience against potential attacks and its suitability for securing IoT communications. We delve into the evaluation of entropy levels in the key generation process to ensure strong cryptographic properties. We also examine the correlation between execution time and QBER to determine the protocol's efficiency and ability to counter timing-based attacks. Additionally, we analyze the efficiency of the keys generated by the BB84 protocol, taking into consideration factors such as key size, generation rate, and computational overhead. These evaluations allow us to assess the protocol's suitability for resource-constrained IoT devices
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.
As the Internet of Things (IoT) networks proliferate, ensuring secure and efficient communication becomes increasingly critical. This paper introduces an enhanced security framework for the MQTT protocol by integrating Quantum Key Distribution (QKD), addressing the vulnerabilities of traditional cryptographic methods. Leveraging the unique properties of QKD, the proposed framework establishes a secure communication channel resilient to eavesdropping and quantum attacks. The proposed framework is evaluated using standard security metrics, demonstrating significant advancements in confidentiality (e.g., unbreakable key exchange), integrity, and authentication. The research findings reveal that integrating QKD considerably improves security while preserving reasonable performance and resource efficiency, offering a strong security for MQTT-based IoT network.
The resource limitations of IoT nodes and the vulnerability of wireless channels to cyberattacks and snooping, the quick spread of Internet of Things (IoT) devices in wireless surroundings has created serious challenges to data security and privacy. The development of quantum computing, which can meritoriously crack classical encryption, is posing a growing threat to recognized cryptographic techniques like RSA and ECC. By applying concepts from quantum mechanics like predicament cloning, quantum cryptography, in particular Quantum Key Distribution (QKD), provides tentatively unbreakable security. In order to integrate lightweight quantum key exchange with traditional IoT communication protocols, this paper proposes a comprehensive Quantum Cryptography Framework (QCF) exactly designed for Wireless IoT networks. The framework is made to preserve energy efficiency while certifying forward secrecy, confidentiality, integrity, and authentication. A performance evaluation in terms of latency, throughput, and resistance to quantum attacks supports our discussion of the architecture, working mechanism, and implementation deliberations. The findings show that, when compared to traditional encryption methods, the suggested QCF greatly improves the security of wireless IoT systems, certifying resilience against oppositional models of the future.
Quantum Key Distribution (QKD) enables information-theoretic secure key exchange by exploiting fundamental quantum phenomena such as superposition and no-cloning. Classical QKD protocols (e.g., BB84) guarantee that any eavesdropping attempt introduces detectable disturbances, but they typically assume stable, high-quality channels and unconstrained devices. In contrast, Internet of Things (IoT) networks present a radically different environment: devices have limited processing power, minimal onboard memory, strict energy budgets, and communicate over highly variable wireless links subject to interference and rapid fading. These constraints lead to elevated quantum bit error rates (QBER), frequent key reconciliation failures, and prohibitive energy costs, all of which jeopardize practical QKD deployment. To address these challenges, we propose an AI-powered QKD protocol specifically optimized for IoT scenarios. Our approach integrates three AI modules: (1) a gradient-boosted regression channel estimator that predicts instantaneous link transmittance using lightweight sensor data and historical photon counts; (2) a reinforcement learning (RL) agent that adaptively tunes photon intensity, basis-selection probability, and reconciliation block size to balance key rate and error rate; and (3) a convolutional neural network (CNN) classifier that selects the optimal Low-Density Parity-Check (LDPC) code rate based on real-time noise characteristics. We simulate a star-topology IoT network of 50 battery-powered devices communicating over 5 km polarization-encoded links with realistic urban loss (0.1–0.3 dB/km) and environmental noise. Compared against a static BB84 baseline, our AI-enhanced protocol reduces average QBER from 4.5% to 2.9%, increases secure key rate from 12.5 kbps to 16.0 kbps, lowers latency by 22%, and reduces energy consumption per key bit by 18%. These improvements persist across channel conditions and device heterogeneity, demonstrating robustness.