Lightweight Cryptographic Protocols for Wireless Sensor Networks
DOI:
https://doi.org/10.15662/IJEETR.2022.0403001Keywords:
Wireless Sensor Networks (WSNs), Lightweight Cryptography, Symmetric Key Cryptography, Asymmetric Key Cryptography, Energy Efficiency, Key Management, Authentication Protocols, Elliptic Curve Cryptography (ECC), Security in Resource-Constrained DevicesAbstract
Wireless Sensor Networks (WSNs) consist of spatially distributed sensor nodes that collect and transmit data for various applications such as environmental monitoring, military surveillance, and healthcare. However, the resource constraints of sensor nodes—limited processing power, memory, and energy—pose significant challenges for implementing traditional cryptographic protocols to secure communications. Lightweight cryptographic protocols have emerged as an essential solution to balance security requirements and resource efficiency in WSNs. This paper reviews recent advancements in lightweight cryptographic schemes specifically designed for WSNs, analyzing symmetric and asymmetric cryptographic techniques, key management strategies, and authentication protocols optimized for lowresource environments. It discusses how these protocols ensure confidentiality, integrity, and authenticity while minimizing energy consumption and computational overhead. A comprehensive literature review is presented to highlight existing approaches, including block ciphers, stream ciphers, hash functions, and elliptic curve cryptography tailored for WSN constraints. The study adopts a systematic methodology, evaluating protocols based on security strength, computational complexity, and energy efficiency through simulation and analytical models. Key findings reveal that while symmetric key cryptography remains the most feasible for WSNs due to its lower computational demands, recent lightweight asymmetric algorithms provide promising trade-offs for secure key exchange. The workflow of implementing these protocols in real-world WSN deployments is outlined. Advantages such as reduced latency and improved network lifetime are weighed against challenges like scalability and key distribution complexity. The paper concludes by discussing future research directions including the integration of machine learning for adaptive security and the development of post-quantum lightweight cryptography for next-generation WSNs.
References
1. Karlof, C., & Wagner, D. (2003). Secure routing in wireless sensor networks: attacks and countermeasures. Ad Hoc Networks, 1(2-3), 293-315.
2. Gura, N., Patel, A., Wander, A., Eberle, H., & Shantz, S. C. (2004). Comparing elliptic curve cryptography and RSA on 8-bit CPUs. Cryptographic Hardware and Embedded Systems - CHES 2004, 119-132.
3. Wander, A. S., Gura, N., Eberle, H., Gupta, V., & Shantz, S. C. (2005). Energy analysis of public-key cryptography for wireless sensor networks. Proceedings of the 3rd IEEE International Conference on Pervasive Computing and
Communications, 324-328.
4. Perrig, A., Szewczyk, R., Wen, V., Culler, D. E., & Tygar, J. D. (2002). SPINS: Security protocols for sensor networks. Wireless Networks, 8(5), 521-534.
5. Al-Shaer, E., Chabukswar, R., & Shafiq, M. (2018). Lightweight cryptography for wireless sensor networks: A survey. IEEE Communications Surveys & Tutorials, 20(3), 2101-2132.
6. Liu, Y., Ning, P., & Du, W. (2017). Attack-resistant location estimation in wireless sensor networks. IEEE Journal on Selected Areas in Communications, 24(2), 395-408.
