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.
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 expansion of Internet of Things (IoT) ecosystems has created a high demand for secure cryptographic solutions, even in a future with quantum computing capabilities. Traditional mappings, such as RSA or Elliptic Curve Cryptography (ECC), are expected to be broken by Shor's algorithm, driving the realization of post-quantum cryptography (PQC). This work presents a simulative and prototypical framework for assessing PQC integration in IoT communication. With the liboqs library and NS-3 network simulator, along with the Python scripting language, we implement both NIST-standardized algorithms, such as Dilithium (for signatures) and Kyber (for key encapsulation), as well as the classical RSA and ECC baselines. IoT networks of 50-500 virtual nodes are simulated based on IEEE 802.15.4/6LoWPAN with RPL routing. Performance attributes, including encryption/decryption time, key length, packet delivery ratio, latency, and energy consumption, are collected and evaluated. Preliminary results indicate that PQC incurs additional handshake and key overhead, but is relatively practical, with an average overhead of15−25msper processed secure transaction. The effort provides a replicable testbed, showcasing what we consider the best and worst PQC has to offer for resource-constrained IoT. Targeted at master's students and researchers, this book provides an applied approach to investigate quantum-resilient security in IoT. It encourages future expansion to hardware-in-the-loop validation on embedded devices.
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/.
This paper presents lightweight Post-Quantum Cryptography (PQC), identifying its importance for a shift from traditional cryptographic schemes, vulnerable to quantum threats, to efficient PQC algorithms. Lattice-based cryptography stands out owing to its small key sizes and computational efficiency, with CRYSTALS-Kyber and NTRU algorithms being substantial representatives for Internet of Things (IoT) applications. However, PQC implementation in IoT environments has various obstacles to overcome. Minimizing energy consumption, scalability, and hardware limitations remain key challenges for PQC smooth integration into these resource-constrained networks. The present review analyzes the state-of-the-art PQC, makes security and performance comparisons among leading algorithms, and evaluates optimization techniques aimed at reducing resource overheads. Algorithmic refinement, hardware acceleration, and hybrid cryptography are also discussed as methods for mitigating these challenges. The results indicate that continuous research and development efforts should be made to improve the PQC technologies, and thus achieve their practical deployment in IoT systems. Quantum threats in IoT will be, hence, prevented with the employment of secure and scalable IoT ecosystems in a post-quantum world.
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.