Quantum-Safe Wireless Sensor Networks: A Post-Quantum Cryptography Framework with Adaptive Security Optimization

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ID: 312597
2026
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Abstract
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.
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Authors Kranthi Kumar Lella
Journal Journal of Computing & Biomedical Informatics
Year 2026
DOI
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URL
https://jcbi.org/index.php/Main/article/view/1253
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