To address the data security challenges and resource constraints faced by low-power sensor networks in Internet of Things(IoT) applications, this study conducted in-depth research on the optimization and application of elliptic curve cryptography(ECC). Centered on lightweight edge-side computation, network-level key collaboration, and adaptive optimization of verification processes, the study proposed a modular security encryption scheme tailored for low-power IoT. The core objective of this scheme was to maximize security strength under strict energy consumption constraints, forming a technical framework composed of three synergistic security modules. Firstly, at the edge-side encryption layer, addressing the limited computational resources of nodes, it introduced a lightweight ECC algorithm with optimized parameter generation, incorporating energyperturbation randomization and verifiable encryption structures to significantly reduce computational load at the edge. Secondly, at the network-level key management layer, to tackle key management challenges in dynamic topologies, it established a hierarchical key management system using distributed key generation and multi-tier derivation strategies, enhancing real-time key updating and system fault tolerance. Finally, at the communication authentication layer, it designed an energy-efficient elastic verification algorithm to adaptively adjust multi-level security validation intensity, achieving a dynamic balance between security and energy efficiency. Experimental results demonstrate that the proposed scheme effectively reduces edge-side computational burden while maintaining strong security, improving system scalability and fault tolerance, thus offering a feasible solution for IoT security that integrates light-weightness, robust security, and real-time performance.