The migration of Internet of Things (IoT) systems to post-quantum cryptography (PQC) is essential to ensure long-term security against quantum enabled adversaries. However, the large computational, memory, and communication overheads of PQC algorithms pose challenges for resource-constrained IoT environments. In practice, IoT platforms span a wide range of capabilities, from battery-powered sensors to gateway devices, making a one-size-fits-all configuration impractical. This paper presents a new methodology for selecting suitable PQC schemes based on RFC 7228 device classes. We introduce the Efficiency-Adjusted Security for Post-Quantum Cryptography (EAS-PQC) metric that considers security strength, latency, energy consumption, memory footprint, communication overhead, and protocol reliability. Device-class-specific constraints and weighting profiles are incorporated to reflect the operational priorities of Class 0, Class 1, and Class 2 IoT devices. Our evaluation primarily uses performance benchmarks from the PQM4 framework, which are based on ARM Cortex-M4 microcontroller profiles, and performance results from several work on similar embedded platforms. Energy consumption is estimated using a constant active power model derived from Cortex-M4 power characteristics. We evaluate multiple PQC candidates, including ML-KEM and ML-DSA, and the results show a quantitative mapping between IoT device classes and PQC schemes. Specifically, Saber-LightSaber is identified as the most suitable option for Class 0 devices, while ML-DSA-87 combined with ML-KEM-768 achieves the highest overall scores for Class 1 and Class 2 devices. Our findings improve feasibility and efficiency by up to 30–40% compared to static baseline configurations. With these findings, we recommend EAS-PQC as a useful tool for the assessment of post-quantum security in industrial IoT systems.
The migration of Internet of Things (IoT) systems to post-quantum cryptography (PQC) is essential to ensure long-term security against quantum enabled adversaries. However, the large computational, memory, and communication overheads of PQC algorithms pose challenges for resource-constrained IoT environments. In practice, IoT platforms span a wide range of capabilities, from battery-powered sensors to gateway devices, making a one-size-fits-all configuration impractical. This paper presents a new methodology for selecting suitable PQC schemes based on RFC 7228 device classes. We introduce the Efficiency-Adjusted Security for Post-Quantum Cryptography (EAS-PQC) metric that considers security strength, latency, energy consumption, memory footprint, communication overhead, and protocol reliability. Device-class-specific constraints and weighting profiles are incorporated to reflect the operational priorities of Class 0, Class 1, and Class 2 IoT devices. Our evaluation primarily uses performance benchmarks from the PQM4 framework, which are based on ARM Cortex-M4 microcontroller profiles, and performance results from several work on similar embedded platforms. Energy consumption is estimated using a constant active power model derived from Cortex-M4 power characteristics. We evaluate multiple PQC candidates, including ML-KEM and ML-DSA, and the results show a quantitative mapping between IoT device classes and PQC schemes. Specifically, Saber-LightSaber is identified as the most suitable option for Class 0 devices, while ML-DSA-87 combined with ML-KEM-768 achieves the highest overall scores for Class 1 and Class 2 devices. Our findings improve feasibility and efficiency by up to 30–40% compared to static baseline configurations. With these findings, we recommend EAS-PQC as a useful tool for the assessment of post-quantum security in industrial IoT systems.
The impending threat posed by quantum computing to classical cryptographic systems has accelerated the need for post-quantum cryptographic (PQC) solutions, particularly within the rapidly expanding domain of the Internet of Things (IoT). As IoT devices operate under severe constraints in terms of memory, processing power, and energy, integrating quantum-resilient algorithms presents both a critical necessity and a formidable challenge. This chapter provides a comprehensive study of PQC implementations on constrained IoT platforms, exploring algorithmic performance, memory consumption, execution time, and energy efficiency across various benchmarking environments. It offers a comparative analysis of bare-metal and RTOSbased deployments, evaluates the trade-offs between security and real-time responsiveness, and investigates power-aware scheduling and duty cycling strategies for secure task execution. Case studies involving smart sensors, medical wearables, and industrial nodes highlight the practical implications and optimizations required for effective PQC integration. Emphasis was placed on hardware-software co-design, library selection, and communication stack alignment to ensure future-ready, quantum-secure IoT deployments. This chapter bridges theoretical cryptographic resilience and applied system-level engineering, laying a foundational framework for scalable and secure post-quantum IoT ecosystems.
Post-quantum cryptographic (PQC) algorithms are being developed to guard against quantum-computing attacks, but their behavior in constrained Internet of Things (IoT) environments remains an important topic of discussion. In this work, we study the impact of deploying PQC protocols in IoT networks using the Open Quantum Safe (liboqs) framework. In particular, key encapsulation and digital signature schemes are evaluated in terms of their computational performance, communication costs, and energy consumption. Our results indicate that although PQC operations can be completed in microseconds using general-purpose processors, substantially larger key and ciphertext sizes introduce significant communication overhead. When mapped to common IoT protocols such as Bluetooth Low Energy (BLE), IEEE 802.15.4 (Zigbee), and LoRa, these larger payloads must be divided into multiple packets. In low-payload LoRa networks, for example, ML-KEM handshakes can require up to 62 packets. This level of fragmentation increases latency and energy consumption, thus potentially affecting reliability. Furthermore, when packet delivery probabilities approaching 99% are achieved, handshake success rates can drop to values approaching 50%. These results suggest that communication metrics, rather than computational performance, pose key challenges to PQC deployment in constrained IoT settings.
The rapid advancement of quantum computing poses a critical threat to classical cryptographic algorithms such as RSA and ECC, particularly in Internet of Things (IoT) devices, where secure communication is essential but often constrained by limited computational resources. This paper investigates the feasibility of deploying post-quantum cryptography (PQC) algorithms on resource-constrained devices. In particular, we implement three PQC algorithms - BIKE, CRYSTALS-Kyber, and HQC - on a lightweight IoT platform built with Raspberry Pi devices. Leveraging the Open Quantum Safe (liboqs) library in conjunction with mbedTLS, we develop quantumsecure key exchange protocols, and evaluate their performance in terms of computational overhead, memory usage, and energy consumption for quantum secure communication. Experimental results demonstrate that the integration of PQC algorithms on constrained hardware is practical, reinforcing the urgent need for quantum-resilient cryptographic frameworks in next-generation IoT devices. The implementation of this paper is available at https://iqsec-lab.github.io/PQC-IoT/.
The rapid advancement of quantum computing poses a critical threat to classical cryptographic algorithms such as RSA and ECC, particularly in Internet of Things (IoT) devices, where secure communication is essential but often constrained by limited computational resources. This paper investigates the feasibility of deploying post-quantum cryptography (PQC) algorithms on resource-constrained devices. In particular, we implement three PQC algorithms - BIKE, CRYSTALS-Kyber, and HQC - on a lightweight IoT platform built with Raspberry Pi devices. Leveraging the Open Quantum Safe (liboqs) library in conjunction with mbedTLS, we develop quantumsecure key exchange protocols, and evaluate their performance in terms of computational overhead, memory usage, and energy consumption for quantum secure communication. Experimental results demonstrate that the integration of PQC algorithms on constrained hardware is practical, reinforcing the urgent need for quantum-resilient cryptographic frameworks in next-generation IoT devices. The implementation of this paper is available at https://iqsec-lab.github.io/PQC-IoT/.
The rapid advancement of quantum computing poses a critical threat to classical cryptographic algorithms such as RSA and ECC, particularly in Internet of Things (IoT) devices, where secure communication is essential but often constrained by limited computational resources. This paper investigates the feasibility of deploying post-quantum cryptography (PQC) algorithms on resource-constrained devices. In particular, we implement three PQC algorithms -- BIKE, CRYSTALS-Kyber, and HQC -- on a lightweight IoT platform built with Raspberry Pi devices. Leveraging the Open Quantum Safe (\texttt{liboqs}) library in conjunction with \texttt{mbedTLS}, we develop quantum-secure key exchange protocols, and evaluate their performance in terms of computational overhead, memory usage, and energy consumption for quantum secure communication. Experimental results demonstrate that the integration of PQC algorithms on constrained hardware is practical, reinforcing the urgent need for quantum-resilient cryptographic frameworks in next-generation IoT devices. The implementation of this paper is available at https://iqsec-lab.github.io/PQC-IoT/.
The impending realization of quantum computing is a threat to the underlying security model of traditional cryptographic infrastructure, especially on the one based on Internet of Things (IoT) and edge computing setups. The post quantum cryptography (PQC) provides quantum resistant protocols that ensure quantum security against a combination of both classical and future quantum attackers, but adopting this technology in edge IoT ecosystems faces serious challenges in terms of resource limitations of low power devices. The paper suggests a performance-security model of PQC in edge IoT explaining the tradeoff between cryptographic robustness and operation efficiency. This model is a synthesis of empirical research in the recent field which looking at the performance of PQC algorithms on limited hardware, the integration issue with lightweight communication protocols, and strategic options such as algorithm optimization, hardware acceleration, hybrid cryptographic schemes, and offloading methods. The objectives of these strategies are to achieve the acceptable latency and energy consumption with the guarantee of quantum resilient security. The framework proposed helps decision making among researchers and practitioners who aim at implementing PQC on distributed resource limited IoT networks. Lastly, the paper also determines the research gaps and future directions to the achievement of scalable, efficient, and robust PQC enabled edge IoT ecosystems.