A Multi-Level Hash-Based Data Integrity Verification and Traceability Scheme for Digital Transformation in Power IoT Networks

Abstract

This paper addresses the unique data security and real-time monitoring requirements in the digital transformation of electric power enterprises, and combines the development characteristics of smart grids to solve the challenges of data integrity verification and anomaly tracing in the electric power Internet of Things (IoT). It proposes a topology-integrated multi-level hash verification and tracing scheme. This method utilizes asymmetric encryption (RSA key generation algorithm KeyGen) and digital signature technology to design a tree-like network architecture (including terminal devices TD, relay devices RD, IoT gateways IoTG, and data servers DS). It employs a multi-level aggregated hash generation algorithm (MLHashGen) to achieve one-time verification of data across the entire network, and precisely locates tampered nodes through an anomaly tracing process. Experimental results show that at a terminal scale of t=300, the computational overhead is reduced to 142.3ms (a 63.3% reduction compared to traditional schemes), the communication overhead is 1,850KB (a 36.5% reduction), and the accuracy rate of anomaly localization reaches 96.5% with a tampering rate of 40% (with a false alarm rate of only 0.8%). The tracing delay of 18.7ms meets the real-time monitoring standards for electric power. This scheme effectively improves data processing efficiency and enterprise benefits. The core contribution lies in eliminating the third-party dependency risks (such as difficulties in defining responsibilities) of centralized systems, establishing a dynamic verification mechanism to block the spread of anomalies, and providing a practical technical framework for electric power enterprises. Future work will focus on optimizing the tracing delay issue in large-scale networks.