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International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV)

Q-IoTGuard: Lightweight Quantum Cryptographic Protocols for Resource-Constrained IoT Devices

K. Malarkodi, G. Sheeba, Sarumathi S, S. Sampath Kumar, B. Vidhya, K. P. Indira

Published May 20, 2026• 0 citations
Publisher

Abstract

The explosion of constrained IoT devices with limited resources has increased the necessity of having efficient security measures to counter both the classical and new quantum threat. In this paper, we introduce Q-IoTGuard, a simple quantum cryptography platform that can be used in heterogeneous IoT networks. The model combines entanglement-assisted quantum key distribution (QKD) with lattice-based post-quantum encryption (PQC) in order to guarantee secure communication with a minimum of computational and energy overhead. The methodology commences with data preprocessing, in which the traffic of IoT and characteristics of the devices are organized, standardized and filtered in order to support the efficient cryptographic operations. Raw data is first fed into quantum-assisted key generation with simplified BB84 protocols with error correction and privacy amplification. Lightweight PQC encrypts then message providing resistance against quantum-enabled attacks. The simulation outcomes show that Q-IoTGuard has a low-key generation time, low latency, low-energy consumption, and high quantum attack resistance among sensors, actuators, and gateway devices. The flow-based architecture, which incorporates preprocessing, key gen, and lightweight encryption would make the framework practical to be deployed on resource-constrained IoT devices. Q-IoTGuard is a new scalable and energy-efficient system of securing next-generation IoT networks that addresses the gap between theoretical quantum security and the practical implementation.

DOI
10.1109/icicv68925.2026.11554871

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The explosion of constrained IoT devices with limited resources has increased the necessity of having efficient security measures to counter both the classical and new quantum threat. In this paper, we introduce Q-IoTGuard, a simple quantum cryptography platform that can be used in heterogeneous IoT networks. The model combines entanglement-assisted quantum key distribution (QKD) with lattice-based post-quantum encryption (PQC) in order to guarantee secure communication with a minimum of computational and energy overhead. The methodology commences with data preprocessing, in which the traffic of IoT and characteristics of the devices are organized, standardized and filtered in order to support the efficient cryptographic operations. Raw data is first fed into quantum-assisted key generation with simplified BB84 protocols with error correction and privacy amplification. Lightweight PQC encrypts then message providing resistance against quantum-enabled attacks. The simulation outcomes show that Q-IoTGuard has a low-key generation time, low latency, low-energy consumption, and high quantum attack resistance among sensors, actuators, and gateway devices. The flow-based architecture, which incorporates preprocessing, key gen, and lightweight encryption would make the framework practical to be deployed on resource-constrained IoT devices. Q-IoTGuard is a new scalable and energy-efficient system of securing next-generation IoT networks that addresses the gap between theoretical quantum security and the practical implementation.
The Internet of Things (IoT) plays a significant role in shaping different aspects of our lives. IoT devices have become increasingly important due to their ability to connect, collect, and analyze data, automate processes, improve safety and efficiency, and deliver personalized experiences. However, the advancement in quantum computer development poses a significant threat to resource-constrained IoT devices. This new generation of computers can break the classic public-key cryptographic schemes and digital signatures implemented in these IoT devices. While protecting IoT devices from quantum computer attacks poses many challenges, researchers are continuously making significant progress in developing lightweight post-quantum cryptographic algorithms for efficient key exchange mechanisms and digital signature algorithms tailored to IoT devices to overcome this issue. This paper proposes Q-SECURE, a post-Quantum resistant Security Enhancing Cryptography for Unified Resource-constrained device Encryption. A novel scheme that enables any IoT system to leverage the assistance of other devices in the network to gain the capability to generate any proposed post-quantum cryptographic key of a given size using distributed and parallel computing.
The rapid proliferation of Internet of Things (IoT) devices has revolutionized digital communication, yet it simultaneously poses unprecedented security challenges due to constrained device capabilities and increasing cyber threats. Conventional cryptographic techniques, while currently effective, are vulnerable to emerging quantum computing technologies that threaten to render classical encryption obsolete. This paper explores the integration of quantum-safe cryptographic techniques within IoT networks to ensure long-term confidentiality, integrity, and authentication. It examines post-quantum cryptographic primitives, including lattice-based, hash-based, multivariate, and code-based schemes, and evaluates their suitability for resource-constrained IoT environments. The study focuses on lightweight implementation strategies, balancing computational efficiency with robust security requirements. Simulation analyses demonstrate that properly optimized quantum safe protocols can provide resilient encryption, key exchange, and digital signature functionalities without overwhelming device resources. Furthermore, the integration of these techniques with IoT communication standards and secure network protocols ensures end-to-end protection across heterogeneous networks. Challenges such as latency, energy consumption, and scalability are addressed, highlighting the necessity of tailored cryptographic solutions for diverse IoT applications. The findings confirm that quantum safe cryptography is essential for future-proofing IoT networks, offering sustainable security measures that remain resilient against both classical and quantum adversaries, thereby supporting the continued expansion of secure and intelligent interconnected systems.
The emergence of quantum computing seriously threatens the security of legacy cryptographic protocols in consumer electronics devices based on the Internet of Things (IoT). These are essential components of mission-critical infrastructures, such as industrial control systems, smart grids, and healthcare. In particular, this work examines how to strengthen the resistance of the IoT to classical and quantum-based cyberattacks by combining deep learning methods with post-quantum cryptography (PQC). To protect key exchange, encryption, and authentication processes in IoT-consumer devices, we will continue to use quantum-resistant cryptographic algorithms, including lattice-based, hash-based, and code-based cryptography. To provide real-time anomaly detection and response capabilities, we suggest a hybrid security framework combining PQC with deep learning-based intrusion detection systems. Our methodology ensures secure communications and data exchanges linked to quantum attacks in the future within IoT systems while leveraging continuous learning over time to allow Intrusion Detection System (IDS) models to adapt to new attack vectors. We suggest optimized algorithms for PQC solutions that are lightweight and suitable for deployment in edge computing nodes and Internet of Things devices, considering the resource-constrained IoT situations where PQC implementation would be difficult. Through comparative studies and simulations, we demonstrate how our integrated PQC-deep learning framework offers an improved IoT security solution that could safeguard vital systems in a world powered by quantum technology. The results shows the key generation time which is 12.5ms, encryption/decryption time 25.3ms, latency 18.7ms, throughput 5000 operations/sec and energy consumption 2.4mJ.
Abstract The increasing advancement of quantum computing threatens the security foundations of classical public-key cryptosystems, particularly RSA and ECC, which remain widely deployed across IoT infrastructures. However, existing post-quantum cryptographic (PQC) schemes are computationally intensive and often unsuitable for resource-constrained IoT devices where memory, CPU cycles, and battery capacity are severely limited. This work proposes EAL-PQCF, an Energy-Efficient Adaptive Lightweight Post-Quantum Cryptographic Framework explicitly designed for constrained IoT environments. The framework introduces a three-mode adaptive PQC strategy consisting of Eco-Secure, Standard-Secure, and Quantum-Threat modes, each selected dynamically based on device battery level, CPU load, and message sensitivity. A Python-based virtual testbed incorporating a simulated IoT device model, lattice-based PQC primitives, an energy estimation module, and an adaptive decision engine is developed for performance evaluation. Experimental results demonstrate that EAL-PQCF achieves 18–36% energy savings, 14–29% reduction in CPU cycles, and significantly improved battery longevity compared to baseline PQC methods. The proposed solution bridges the gap between high-security quantum-resistant cryptography and the practical constraints of IoT devices, offering a scalable pathway for secure next-generation IoT deployments.
The emergence of quantum computing threatens classical cryptographic systems, including RSA and ECC, potentially compromising the security of pervasive Internet of Things (IoT) deployments. Resourceconstrained IoT devices—such as sensors, embedded controllers, and microcontrollers—face significant challenges in adopting post-quantum cryptographic (PQC) protocols due to computational, memory, and energy limitations. This paper proposes AQ-PQC, an adaptive lightweight hybrid key exchange protocol combining Kyber lattice-based KEM and lightweight elliptic curve cryptography (ECC), specifically designed for constrained devices. AQ-PQC introduces a dynamic parameter tuning algorithm that adjusts key sizes, handshake rounds, and compression ratios based on real-time device state and network conditions. Formal security analysis under the IND-CCA model demonstrates quantum-resistance and forward secrecy. Extensive hardware implementation on Raspberry Pi 4 and ESP32 devices reveals a significant reduction in handshake latency, energy consumption, and memory footprint compared to conventional PQC protocols. The proposed framework provides a practical, reproducible, and secure methodology for post-quantum IoT communications, supporting heterogeneous and resource-limited networks.
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.