Eco-conscious multi-factor authentication protocols for energy-aware wireless networks

• Introduces 3EDCT (Energy-Efficient Elliptic Diffie Clustering Technique) that balances security and energy efficiency in WSNs. • Combines Elliptic Curve Diffie–Hellman (ECDH) with Energy-Efficient Hybrid Clustering Technique (EEHCT) for secure key exchange and optimal cluster formation. • Dynamic cluster head rotation based on residual energy and proximity enhances network longevity. • Multi-factor authentication ensures robust node verification against common WSN attacks. • Demonstrates improved performance with reduced energy usage, extended lifetime (36,865 s), lower latency (0.114 s), and minimized overhead (1472 bits, 4.92 ms). The rapid advancement of wireless technologies has enabled the widespread deployment of wireless sensor networks (WSNs) in various applications, including environmental monitoring, military surveillance, and smart infrastructure. However, due to their decentralized design, limited energy resources, and open wireless communication channels, WSNs are extremely vulnerable to attacks such as eavesdropping, impersonation, and tampering. Existing security solutions frequently ignore the fundamental energy limits of sensor nodes, resulting in rapid battery depletion and shortened network longevity. To solve this issue, the goal of this research is to provide an Energy-Efficient Elliptic Diffie Clustering Technique (3EDCT) method that is suited for energy-conscious WSNs that balance security robustness with low energy usage. The proposed technique comprises two major components: Elliptic Curve Diffie–Hellman (ECDH) and Energy-Efficient Hybrid Clustering Technique (EEHCT). Nodes are grouped into optimum clusters using EEHCT, with cluster heads chosen depending on residual energy and proximity. EEHCT rotates cluster heads dynamically to avoid early energy exhaustion. During authentication, ECDH is utilized to exchange public keys securely and efficiently between nodes and cluster chiefs. Multi-factor authentication is used to verify the identification of nodes. The model is evaluated based on parameters such as energy usage, node longevity, and authentication latency. The results reveal that the 3EDCT method reduces overall energy usage, increases network lifetime (36,865 s), and achieves a significant reduction in latency (0.114 s), as well as a reduction in communication and computation overhead (1472 bits and 4.92 ms) compared to baseline models. The 3EDCT method, combined with ECDH and EEHCT, offers a scalable, secure, and energy-aware solution for next-generation WSN applications.