Quantum computing poses a significant threat to Internet of Things (IoT) communications that rely on classical cryptographic algorithms such as RSA, Diffie–Hellman, and Elliptic Curve Cryptography (ECC). These algorithms are vulnerable to Shor’s algorithm, making long-term data security uncertain, particularly for IoT devices with extended operational lifespans. Post-quantum cryptographic (PQC) algorithms offer resistance to quantum attacks; however, their deployment on resource-constrained IoT devices remains challenging due to limitations in processing power, memory, and energy consumption. This study benchmarks seven Key Encapsulation Mechanisms (KEMs) ML-KEM, Kyber, NTRU, BIKE, Classic McEliece, FrodoKEM, and sntrup761 across key generation, encapsulation, and decapsulation operations. Experiments were conducted using the liboqs library in a virtualized Linux environment running WSL2 to simulate constrained computing conditions. Results revealed substantial performance differences among the algorithms. ML-KEM-512 achieved the best overall performance, completing all operations in under 14 µs, while Kyber-512 showed similar efficiency. NTRU provided the fastest encapsulation but incurred significantly higher key-generation costs. BIKE, FrodoKEM, and Classic McEliece exhibited execution times unsuitable for real-time IoT applications. Overall, lattice-based schemes, particularly ML-KEM and Kyber, emerged as the most practical PQC solutions for resource-constrained IoT environments. The findings also demonstrate the usefulness of virtualized benchmarking for deployment planning.
Quantum computing poses a significant threat to Internet of Things (IoT) communications that rely on classical cryptographic algorithms such as RSA, Diffie–Hellman, and Elliptic Curve Cryptography (ECC). These algorithms are vulnerable to Shor’s algorithm, making long-term data security uncertain, particularly for IoT devices with extended operational lifespans. Post-quantum cryptographic (PQC) algorithms offer resistance to quantum attacks; however, their deployment on resource-constrained IoT devices remains challenging due to limitations in processing power, memory, and energy consumption. This study benchmarks seven Key Encapsulation Mechanisms (KEMs) ML-KEM, Kyber, NTRU, BIKE, Classic McEliece, FrodoKEM, and sntrup761 across key generation, encapsulation, and decapsulation operations. Experiments were conducted using the liboqs library in a virtualized Linux environment running WSL2 to simulate constrained computing conditions. Results revealed substantial performance differences among the algorithms. ML-KEM-512 achieved the best overall performance, completing all operations in under 14 µs, while Kyber-512 showed similar efficiency. NTRU provided the fastest encapsulation but incurred significantly higher key-generation costs. BIKE, FrodoKEM, and Classic McEliece exhibited execution times unsuitable for real-time IoT applications. Overall, lattice-based schemes, particularly ML-KEM and Kyber, emerged as the most practical PQC solutions for resource-constrained IoT environments. The findings also demonstrate the usefulness of virtualized benchmarking for deployment planning.
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/.
Current improvements in quantum computing present a substantial challenge to classical cryptographic systems, which typically rely on problems that can be solved in polynomial time using quantum algorithms. Consequently, post-quantum cryptography (PQC) has emerged as a promising solution to emerging quantum-based cryptographic challenges. The greatest threat is public-key cryptosystems, which are primarily responsible for key exchanges. In PQC, key encapsulation mechanisms (KEMs) are crucial for securing key exchange protocols, particularly in Internet communication, virtual private networks (VPNs), and secure messaging applications. CRYSTALS-Kyber and NTRU are two well-known PQC KEMs offering robust security in the quantum world. However, even when quantum computers are functional, they are not easily accessible. IoT devices will not be able to utilize them directly, so there will still be a requirement to protect IoT devices from quantum attacks. Concerns such as limited computational power, energy efficiency, and memory constraints in devices such as those used in IoTs, embedded systems, and smart cards limit the use of these techniques in constrained environments. These concerns always arise there. To address this issue, this study conducts a broad comparative analysis of Kyber and NTRU, with special focus on their security, performance, and implementation efficiency in such environments (IOT/constrained environments). In addition, a case study was conducted by applying KEMs to a low-power embedded device to analyze their performance in real-world scenarios. These results offer an important comparison for cyber security engineers and cryptographers who are involved in integrating post-quantum cryptography into resource-constrained 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/.
The recent introduction of Google’s Willow quantum chip has demonstrated remarkable computational capabilities, solving problems in microseconds that would take classical computers millions of years. As quantum computers advance toward cryptographic relevance, existing encryption algorithms become vulnerable to attacks that could break them within seconds or minutes, rendering current cryptographic protections ineffective. This necessitates the establishment of post-quantum cryptography (PQC) standards to secure systems in the quantum era. This study evaluates the performance of NIST-standardized PQC algorithms ML-KEM (512, 768, 1024) and ML-DSA (2, 3, 5) on a Raspberry Pi 4 Model B, representing baseline IoT device capabilities. Using the Liboqs library, each algorithm was executed across 1000 iterations in a real-world wireless network environment connected to a router, accounting for practical network conditions such as packet loss, latency, and jitter to assess computational feasibility under resource-constrained conditions. Experimental results demonstrate the practical viability of PQC algorithms in IoT environments. ML-KEM-512 achieves encapsulation in 55.76 μs and decapsulation in 56.15 μs, with key generation in 123.78 μs (median), while ML-DSA-44 completes signature generation in 379.83 μs and verification in 159.38 μs. These findings confirm that both ML-KEM and ML-DSA algorithms offer efficient and rapid performance, making them suitable candidates for securing IoT devices against quantum threats.
The emergence of large-scale quantum computing presents an imminent threat to contemporary public-key cryptosystems, with quantum algorithms such as Shor’s algorithm capable of efficiently breaking RSA and elliptic curve cryptography (ECC). This vulnerability has catalyzed accelerated standardization efforts for post-quantum cryptography (PQC) by the U.S. National Institute of Standards and Technology (NIST) and global security stakeholders. While theoretical security analysis of these quantum-resistant algorithms has advanced considerably, comprehensive real-world performance benchmarks spanning diverse computing environments—from high-performance cloud infrastructure to severely resource-constrained IoT devices—remain insufficient for informed deployment planning. This paper presents the most extensive cross-platform empirical evaluation to date of NIST-selected PQC algorithms, including CRYSTALS-Kyber and NTRU for key encapsulation mechanisms (KEMs), alongside BIKE as a code-based alternative, and CRYSTALS-Dilithium and Falcon for digital signatures. Our systematic benchmarking framework measures computational latency, memory utilization, key sizes, and protocol overhead across multiple security levels (NIST Levels 1, 3, and 5) in three distinct hardware environments and various network conditions. Results demonstrate that contemporary server architectures can implement these algorithms with negligible performance impact (<5% additional latency), making immediate adoption feasible for cloud services. In contrast, resource-constrained devices experience more significant overhead, with computational demands varying by up to 12× between algorithms at equivalent security levels, highlighting the importance of algorithm selection for edge deployments. Beyond standalone algorithm performance, we analyze integration challenges within existing security protocols, revealing that naive implementation of PQC in TLS 1.3 can increase handshake size by up to 7× compared to classical approaches. To address this, we propose and evaluate three optimization strategies that reduce bandwidth requirements by 40–60% without compromising security guarantees. Our investigation further encompasses memory-constrained implementation techniques, side-channel resistance measures, and hybrid classical-quantum approaches for transitional deployments. Based on these comprehensive findings, we present a risk-based migration framework and algorithm selection guidelines tailored to specific use cases, including financial transactions, secure firmware updates, vehicle-to-infrastructure communications, and IoT fleet management. This practical roadmap enables organizations to strategically prioritize systems for quantum-resistant upgrades based on data sensitivity, resource constraints, and technical feasibility. Our results conclusively demonstrate that PQC is deployment-ready for most applications, provided that implementations are carefully optimized for the specific performance characteristics and security requirements of target environments. We also identify several remaining research challenges for the community, including further optimization for ultra-constrained devices, standardization of hybrid schemes, and hardware acceleration opportunities.