Lightweight post-quantum cryptography for energy-constrained wireless sensor networks
Ritesh Shrivastavritesharsh15@gmail.comDepartment of Computer Science & EngineeringAnjuman College of Engineering & TechnologyNagpur, Maharashtra, 440022, IndiaView full profile → , Prajwal Gaikwadprajwaltrk@gmail.comDepartment of Artificial Intelligence & Data ScienceAISSMS Institute of Information TechnologyPune, Maharashtra, 411001, IndiaView full profile → , *Ravi ThangjamCorresponding authorravithangjam@outlook.comSchool of BusinessAditya UniversitySurampalem, Kakinada District, Andhra Pradesh, 533437, IndiaView full profile → , G. Vijaya Kumargvijayakumar@outlook.comDepartment of Computer Science and EngineeringPragati Engineering CollegeSurampalem, Kakinada District, Andhra Pradesh, 533437, IndiaView full profile → , Amruta Prasad Kharadeamruta.kharade@vit.eduDepartment of Engineering Science and HumanitiesVishwakarma Institute of TechnologyPune, Maharashtra, 411037, IndiaView full profile → , Preeti Pandurang Kalepreetikale2025@gmail.comDepartment of Electronics and Computer EngineeringCSMSS Chh. Shahu College of EngineeringChhatrapati Sambhajinagar, Maharashtra, 431012, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Apr 2026
- Published Online:
- 31 Oct 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JDMSC-3018
- Pages:
- 3899–3912
Abstract
The very fast development of quantum computing is a serious threat to traditional cryptographic solutions that are used in wireless sensor networks (WSNs), especially those that have severe energy and computing requirements. The paper presents a lightweight post-quantum cryptographic (PQC) system that is specific to the resource-constrained WSN. The aim is to provide quantum-resistant security with a minimum energy requirement, latency, and memory overhead. The solution proposed combines lattice-based primitives, optimized key generating schemes and compact encryption schemes, with mathematical modeling to validate their performance. Experimental assessment shows that the framework has a security against quantum attacks, consumes less energy by 28.4% and latency is less by 31.2% than traditional PQC instantiations. The framework also ensures scalability with heterogeneous sensor nodes.
Keywords
Subject Classifications
References
References
[1] C.-L. Chen, K.-W. Zeng, W.-Y. Li, C.-F. Lee, L.-C. Liu, and Y.-Y. Deng, “Lightweight post-quantum cryptography: Applications and countermeasures in Internet of Things, blockchain, and e-learning,” Engineering Proceedings, vol. 103, no. 1, Art. no. 14 (2025), doi: 10.3390/engproc2025103014.
[2] M. Kara, K. Karampidis, S. Panagiotakis, M. Hammoudeh, M. Felemban, and G. Papadourakis, “Lightweight and efficient post quantum key encapsulation mechanism based on Q-problem,” Electronics, vol. 14, no. 4, Art. no. 728 (2025), doi: 10.3390/electronics14040728.
[3] H. P. Nguyen and Y. Chen, “Lightweight, post-quantum secure cryptography based on Ascon: Hardware implementation in automotive applications,” Electronics, vol. 13, no. 22, Art. no. 4550 (2024), doi: 10.3390/electronics13224550.
[4] L. Zhou, M. Kang, and W. Chen, “Lightweight security transmission in wireless sensor networks through information hiding and data flipping,” Sensors, vol. 22, no. 3, Art. no. 823 (2022), doi: 10.3390/s22030823.
[5] C. S. Kumar and A. P. Singh, “A blockchain-based auction framework for sustainable waste management: Utilizing non-fungible tokens (NFT) and zero knowledge proofs (ZKPs) for enhanced authentication,” Journal of Information and Optimization Sciences, vol. 46, no. 6, pp. 1891–1899 (2025), doi: 10.47974/JIOS-2018.
[6] I. Radhakrishnan, S. Jadon, and P. B. Honnavalli, “Efficiency and security evaluation of lightweight cryptographic algorithms for resource-constrained IoT devices,” Sensors, vol. 24, no. 12, Art. no. 4008 (2024), doi: 10.3390/s24124008.
[7] C. M. Anish, A. Jadhav, H. N. Datir, G. S. Mate, A. Ashirova, and A. Rawat, “Lightweight AI-supported ECC algorithms for security in IoT and edge devices,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 29, no. 2-B, pp. 779–787 (2026), doi: 10.47974/JDMSC-2524.
[8] G. Fitzgibbon and C. Ottaviani, “Constrained device performance benchmarking with the implementation of post-quantum cryptography,” Cryptography, vol. 8, no. 2, Art. no. 21 (2024), doi: 10.3390/cryptography8020021.
[9] M. U. Mushtaq, H. Venter, A. Singh, and M. Owais, “Advances in energy harvesting for sustainable wireless sensor networks: Challenges and opportunities,” Hardware, vol. 3, no. 1, Art. no. 1 (2025), doi: 10.3390/hardware3010001.
[10] W. N. Anandpwar, S. M. Barhate, and M. P. Dhore, “Designing an efficient machine learning-based intrusion detection system for enhanced cyber security in modern networks,” International Journal on Advanced Computer Theory and Engineering, vol. 14, no. 1, pp. 70–75 (2025), doi: 10.65521/ijacte.v14i1.216.
[11] R. C. Poonia, R. Almakki, A. K. J. Saudagar, A. Altameem, and M. Albathan, “An optimization approach for real-time object detection in IoT devices through edge computing and deep learning,” Journal of Information and Optimization Sciences, vol. 45, no. 5, pp. 1465–1475 (2024), doi: 10.47974/JIOS-1768.
[12] T.-G. Sorescu, V.-M. Chiriac, M.-A. Stoica, C.-R. Comsa, I.-G. Soroaga, and A. Contac, “Comparative performance analysis of lightweight cryptographic algorithms on resource-constrained IoT platforms,” Sensors, vol. 25, no. 18, Art. no. 5887 (2025), doi: 10.3390/s25185887.
