ABSTRACT Smart cities are built on a vast interconnected network of Internet of things (IoT), edge and cloud systems to optimise urban services and enhance the quality of life for the residents. However, this integration of cyber‐physical infrastructure expands the attack surface, making it vulnerable to advanced cyber threats. The most notable emerging threat is quantum computers, which can break the classical cryptographic algorithms, such as RSA and ECC, that form the foundation of cybersecurity. Integrating liboqs execution benchmarks with an analytical network fragmentation model simulated with NS‐3, evaluating NIST‐approved PQC key encapsulation mechanisms, ML‐KEM (Kyber512/768/1024), HQC (128/192/256) and classic McEliece variants, alongside signature schemes ML‐DSA (Dilithium), Falcon and SLH‐DSA (SPHINCS+) within a smart city network. We also extended the benchmarking to include NIST's SP 800‐230 draft and provide preliminary benchmarks of the six new parameter sets. To assess embedded feasibility, all algorithms are additionally executed on the ESP32 P4 microcontroller, measuring timing, energy consumption and memory under resource‐constrained conditions. This dual platform methodology enables cross‐validation of network‐level overhead and hardware‐level performance. Results show consistent behaviour across platforms. ML KEM 512 (NIST Security Level 1) provides the best KEM performance, with key generation at 7.2 µs (NS‐3) and 122.6 ms (ESP32 P4), and similarly efficient encapsulation/decapsulation. ML DSA 44 (NIST Security Level 2) achieves the fastest signatures at 64 µs on NS‐3 and 490.6 ms on ESP32 P4. These findings provide evidence‐based guidelines for deploying postquantum cryptography across smart city IoT–Edge–Cloud infrastructures, emphasising crypto‐agility and hybrid cryptography for smart city networks.
ABSTRACT Smart cities are built on a vast interconnected network of Internet of things (IoT), edge and cloud systems to optimise urban services and enhance the quality of life for the residents. However, this integration of cyber‐physical infrastructure expands the attack surface, making it vulnerable to advanced cyber threats. The most notable emerging threat is quantum computers, which can break the classical cryptographic algorithms, such as RSA and ECC, that form the foundation of cybersecurity. Integrating liboqs execution benchmarks with an analytical network fragmentation model simulated with NS‐3, evaluating NIST‐approved PQC key encapsulation mechanisms, ML‐KEM (Kyber512/768/1024), HQC (128/192/256) and classic McEliece variants, alongside signature schemes ML‐DSA (Dilithium), Falcon and SLH‐DSA (SPHINCS+) within a smart city network. We also extended the benchmarking to include NIST's SP 800‐230 draft and provide preliminary benchmarks of the six new parameter sets. To assess embedded feasibility, all algorithms are additionally executed on the ESP32 P4 microcontroller, measuring timing, energy consumption and memory under resource‐constrained conditions. This dual platform methodology enables cross‐validation of network‐level overhead and hardware‐level performance. Results show consistent behaviour across platforms. ML KEM 512 (NIST Security Level 1) provides the best KEM performance, with key generation at 7.2 µs (NS‐3) and 122.6 ms (ESP32 P4), and similarly efficient encapsulation/decapsulation. ML DSA 44 (NIST Security Level 2) achieves the fastest signatures at 64 µs on NS‐3 and 490.6 ms on ESP32 P4. These findings provide evidence‐based guidelines for deploying postquantum cryptography across smart city IoT–Edge–Cloud infrastructures, emphasising crypto‐agility and hybrid cryptography for smart city networks.
Abstract. As the threat of quantum computing to classical cryptography grows, the transition to post-quantum cryptographic (PQC) systems becomes essential—particularly for smart city infrastructures that rely heavily on secure, real-time sensor data. This paper investigates the performance of PQC algorithms currently in the final stages of standardization by the U.S. National Institute of Standards and Technology (NIST), focusing on their deployment in resource-constrained Internet of Things (IoT) devices. Leveraging real-world smart city sensor datasets, we develop a research prototype that simulates a realistic urban sensing scenario, using Raspberry Pi 3 and Pi Zero 2 W devices to cryptographically secure and transmit data to a central server. Experimental results demonstrate that the Kyber family is the most efficient for key encapsulation tasks, while Dilithium and Falcon offer strong performance for digital signatures. In contrast, PQC algorithms such as McEliece, HQC, and Rainbow exhibit substantial computational overhead—especially at higher security levels—limiting their suitability for time-sensitive or low-power environments. Our findings highlight the practical implications of PQC adoption in smart cities and provide evidence-based guidance for selecting efficient quantum-safe algorithms for real-world urban sensor networks.
Quantum computing poses an existential threat to classical public-key cryptography, particularly RSA and elliptic-curve systems, which form the backbone of secure communication, authentication, and digital trust. Once scalable quantum computers emerge, algorithms such as Shor’s will be capable of breaking these schemes, jeopardizing confidentiality and integrity across the internet and enterprise systems. Post-quantum cryptography (PQC) offers a viable defense, providing quantum-resistant algorithms that can be implemented on today’s hardware and protocols. Recent standardization milestones—including NIST’s approval of ML-KEM (Kyber) for key establishment, ML-DSA (Dilithium) and SLH-DSA (SPHINCS+) for signatures, and the selection of HQC as a complementary KEM—mark a turning point for practical adoption. This paper surveys the quantum threat model, algorithm families, performance trade-offs, and integration patterns such as hybrid modes and crypto-agile architectures. It further outlines a phased migration roadmap for enterprises, emphasizing harvest-now-decrypt-later risks and compliance imperatives. By bridging technical, operational, and policy perspectives, the study provides actionable guidance to prepare organizations for a secure and quantum-resilient future.
Smart Cities rely on high-density digital infrastructures that include Internet of Things (IoT) devices, Artificial Intelligence (AI), cloud computing, digital identity systems, and operational technology. Although these systems improve efficiency and sustainability, they also provide a large cyber-physical attack surface. The problem is exacerbated by the advent of quantum computing, as popular public-key ciphers like RSA and elliptic-curve cryptography can be broken using quantum algorithms such as Shor's algorithm (Shor, 1994; Mosca, 2018). Smart cities rely on long-term data confidentiality, certificate-based trust, and remote management of critical infrastructure. This presents a strategic cyber resilience challenge. This thesis examines the impact of quantum technology on smart cities' cyber resilience, as well as how quantum-safe mechanisms can be integrated into urban digital infrastructure. The updated proposal now includes a critical literature review, case reasoning by comparison, a threat and vulnerability matrix, and a simulated BB84 quantum key distribution demonstration. According to NIST (2024b, 2024c, 2024d) and Pirandola et al. (2020), this thesis supports post-quantum cryptography (PQC) NIST standards FIPS 203, FIPS 204, and FIPS 205 as a scalable software migration strategy and quantum key distribution (QKD) as a selective protection strategy for high-value fixed communication links. The analysis demonstrates that quantum-safe resilience cannot be achieved solely through one technology. Any practical smart city transition must include a cryptographic inventory, data lifetime assessment, risk-based prioritization of critical services, hybrid migration, continuous monitoring, and governance. According to the simulation, the quantum bit error rate increases during the intercept-resend attack, alerting Alice and Bob to the eavesdropping activity and allowing them to discard the common key. The proposed framework integrates post-quantum cryptography for a wide range of software and cloud services, quantum key distribution for specific critical infrastructure links, and NIST Cybersecurity Framework 2.0 governance functions to ensure ongoing operational resilience.
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.
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 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.