Quantum computing poses a significant threat to Wireless Sensor Networks (WSNs) by undermining traditional cryptographic algorithms such as RSA and Elliptic Curve Cryptography (ECC). This work proposes a quantum-safe architecture for WSNs that integrates post-quantum cryptography (PQC) with lightweight IoT protocols to ensure long-term confidentiality, authenticity, and resilience. The framework leverages ML-KEM for key encapsulation and ML-DSA/SLH-DSA for signatures, and seamlessly integrates with EDHOC, OSCORE, and COSE. A novel Efficient Adaptive Parameter Selection (EAPS) mechanism dynamically adjusts cryptographic strength to balance security, energy consumption, and latency under varying network conditions. Experimental evaluation demonstrates that ciphertext fragmentation (8–27 pieces) results in manageable completion times of 4–10 seconds, while join operations consume only 0.005–0.03 J per cryptographic handshake event, while system-level energy consumption including network overhead is higher (~1.0–1.4 J per join cycle depending on hop count and retransmissions). Battery lifetime projections under steady-state sensing workloads range from approximately 115–280 months for low-duty-cycle operation, whereas realistic deployment conditions with periodic communication yield effective lifetimes of 11.5–24 months. Security analysis confirms robust resistance against downgrade attacks and Harvest-Now-Decrypt-Later (HNDL) threats. Moreover, EAPS reduces risk scores by over 50% compared to fixed schemes with less than 10% additional energy overhead, and batch signature verification improves scalability by increasing throughput from ~1,600 to ~2,800 verifications per second. Overall, the proposed framework demonstrates that WSNs can achieve quantum-resistant security with minimal performance trade-offs, ensuring readiness for the post-quantum era.
Quantum computing poses a significant threat to Wireless Sensor Networks (WSNs) by undermining traditional cryptographic algorithms such as RSA and Elliptic Curve Cryptography (ECC). This work proposes a quantum-safe architecture for WSNs that integrates post-quantum cryptography (PQC) with lightweight IoT protocols to ensure long-term confidentiality, authenticity, and resilience. The framework leverages ML-KEM for key encapsulation and ML-DSA/SLH-DSA for signatures, and seamlessly integrates with EDHOC, OSCORE, and COSE. A novel Efficient Adaptive Parameter Selection (EAPS) mechanism dynamically adjusts cryptographic strength to balance security, energy consumption, and latency under varying network conditions. Experimental evaluation demonstrates that ciphertext fragmentation (8–27 pieces) results in manageable completion times of 4–10 seconds, while join operations consume only 0.005–0.03 J per cryptographic handshake event, while system-level energy consumption including network overhead is higher (~1.0–1.4 J per join cycle depending on hop count and retransmissions). Battery lifetime projections under steady-state sensing workloads range from approximately 115–280 months for low-duty-cycle operation, whereas realistic deployment conditions with periodic communication yield effective lifetimes of 11.5–24 months. Security analysis confirms robust resistance against downgrade attacks and Harvest-Now-Decrypt-Later (HNDL) threats. Moreover, EAPS reduces risk scores by over 50% compared to fixed schemes with less than 10% additional energy overhead, and batch signature verification improves scalability by increasing throughput from ~1,600 to ~2,800 verifications per second. Overall, the proposed framework demonstrates that WSNs can achieve quantum-resistant security with minimal performance trade-offs, ensuring readiness for the post-quantum era.
Ensuring the confidentiality of communication is of paramount significance. Traditionally, cryptographic practices for Wireless Sensor Networks (WSN) have been primarily based on classical cryptography like RSA and Elliptic Curve, which are potentially susceptible to cyber attacks from future quantum computers with enough computing power. To ensure the protection and safety of inter-node communication in WSNs, it becomes imperative to employ a Post-Quantum Cryptography (PQC) algorithm. This paper presents post-quantum low-energy adaptive clustering hierarchy (PQ-LEACH), an advanced secure wireless communication protocol based on the LEACH protocol. By integrating post-quantum cryptography, specifically Kyber’s key encapsulation method, and a key update system, PQ-LEACH effectively enhances the security of communication and mitigates various WSN attacks. Additionally, a comprehensive performance analysis of PQ-LEACH, including its impact on network energy efficiency and longevity, is conducted. The results demonstrate the trade-offs between enhanced security measures and operational performance, providing critical insights for the deployment of secure and efficient WSNs in a quantum-threatened landscape.
The rapid expansion of the Internet of Things (IoT) has introduced unprecedented cybersecurity challenges, as traditional cryptographic methods struggle to provide both efficiency and quantum resistance in resource-constrained environments. This research introduces Adaptive Quantum Cryptography (AQC), a novel security framework that integrates Quantum Key Distribution (QKD), Post-Quantum Cryptography (PQC), Quantum Random Number Generators (QRNGs), and AI-driven dynamic adaptation to safeguard IoT networks against evolving cyber threats. Unlike classical encryption techniques such as RSA and ECC, which are vulnerable to quantum attacks, AQC leverages quantum mechanical principles—such as superposition, entanglement, and the no-cloning theorem—to ensure provably secure key exchange and data encryption. The proposed AQC system dynamically adjusts cryptographic protocols based on real-time network conditions, computational resources, and threat intelligence, optimizing security without imposing excessive overhead. Experimental evaluations demonstrate that AQC achieves a 70% improvement in key exchange efficiency, a 50% reduction in computational load, and a 95% resilience rate against quantum attacks compared to conventional encryption methods. Additionally, the integration of QRNGs enhances cryptographic key entropy, while AI-driven anomaly detection enables proactive threat mitigation. This framework is particularly suited for next-generation IoT applications, including smart grids, autonomous vehicles, and industrial automation, where security, scalability, and energy efficiency are critical. By combining quantum-resistant algorithms with adaptive security mechanisms, AQC provides forward secrecy, resistance to quantum adversaries, and robust authentication, ensuring long-term protection for IoT ecosystems in the post-quantum era. The findings underscore AQC’s potential as a foundational security architecture for future quantum-safe IoT networks.
The Google Quantum AI whitepaper [1] established that the secp256k1 elliptic curve discrete logarithm problem (ECDLP-256) the signature primitive securing the majority of public blockchain networks can be broken with fewer than 500,000 physical qubits in approximately nine minutes on a fast-clock cryptographically relevant quantum computer (CRQC), a roughly 20-fold reduction from prior estimates. That analysis addresses cryptocurrency nodes and does not model the structurally distinct risk profile of IoT/WSN nodes participating in blockchain networks. This paper closes that gap. We demonstrate that gateway-mediated transaction submission, combined with the duty-cycle wakeup latency endemic to IEEE 802.15.4-class sensor nodes, can extend the on-spend attack window beyond Bitcoin’s ten-minute block time making constrained WSN nodes more vulnerable to on-spend attacks than standard cryptocurrency clients for certain deployment configurations. We introduce a formal HNDL Risk Score (HRS) that jointly quantifies harvest-now/decrypt-later exposure, on-spend vulnerability, and migration feasibility as a function of node hardware class and deployment lifespan. We benchmark all four NIST-standardised post-quantum cryptography algorithms (ML-KEM-512, ML-DSA-44, FN-DSA/FALCON-512, SLH-DSA-128s) on representative WSN hardware (Raspberry Pi Pico RP2040 and ESP32) and identify FN-DSA/FALCON-512 as the superior candidate for WSN-blockchain transaction authentication, offering 666-byte signatures at 71.6 ms mean signing time on Cortex-M0+ hardware. A concrete, tiered migration roadmap is proposed for healthcare WSN, industrial IIoT, and smart city sensor deployments.
The intersection of security and sustainability within wireless sensor networks (WSNs) underscores pivotal factors such as energy efficiency, resource optimization, energy waste reduction, and the sustained integrity of network infrastructure. This interplay ensures that deployments are not just efficient but also ecologically sound. WSNs comprise autonomously dispersed sensors linked to battery-powered devices, facilitating wireless data transmission. The optimization of WSNs through Fog and Edge Computing signifies a paradigm shift, diminishing reliance on central cloud servers. This adaptive strategy enhances WSN efficiency across diverse environmental conditions by streamlining data transmission to centralized cloud servers. In cryptographic systems, conventional approaches reliant on mathematical algorithms to secure communication channels encounter vulnerabilities. Quantum cryptography presents a more robust alternative to conventional methods, while post-quantum cryptography (PQC) employs algorithms resilient to both traditional and quantum threats. This chapter introduces a novel approach for mutual authentication and generating session keys in communications between WSN nodes. We use Super singular Hyperelliptic Curve Cryptography (HECC) with a small size by exchange key Diffie-Hellman (DH) to improve security in IoT and WSN. This method provides a promising mix of quantum resistance and integration into conventional approaches.
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 emergence of quantum computing is expected to break many conventional cryptographic algorithms currently used for authentication and secure communication. Existing security mechanisms in Next Generation Networks (NGNs), including 5G, IoT, smart healthcare, and cloud-based systems, are increasingly vulnerable to future quantum attacks. This research presents a lightweight and efficient Post-Quantum Cryptography (PQC) based authentication framework specifically designed for next generation network environments. The proposed framework combines quantum-resistant cryptographic techniques with optimized authentication procedures to provide secure identity verification, confidential communication, and attack resistance with minimal computational complexity. The model emphasizes reduced overhead, faster authentication response, and scalability for resource-constrained devices. Security analysis shows that the framework can effectively defend against replay attacks, impersonation attacks, session hijacking, and quantum-based cryptanalytic threats. Experimental evaluation indicates that the proposed approach achieves improved security performance while maintaining low latency and reduced resource consumption, making it suitable for practical deployment in future intelligent communication networks.