Construction of Big Data Information Security Protection System in Industrial Internet Environment

With the continuous development and integration of information technology and industrialization-related technologies, industrial Internet control system security attacks occur frequently, and it is more and more important to build an information security protection system. This study focuses on the research improvement from two aspects of access control and intrusion prevention and designs an industrial Internet security access control strategy based on the homomorphic encryption algorithm of the Hyper Elliptic Curve Cryptosystem (HCC) and the key splitting algorithm based on threshold. Meanwhile, the convolutional neural network, two-way gating loop unit, and multi-head attention mechanism are integrated to construct the CMAG intrusion detection model. The encryption algorithm and CMAG model are applied and analyzed. The encryption and decryption times of this paper's algorithm are both relatively smooth, with an average time consumption of about 1.93ms and 0.46ms, respectively, and significantly better than other algorithms with the increase in the number of bits. The throughput of this paper's encryption algorithm is 13.68 KB/s, which is approximately 2 times, 19 times, and 29 times higher than the throughput of GM, ElGamal, and Paillier algorithms, respectively. The other algorithms cannot match its throughput rate during decryption. The CMAG model has an accuracy of 99.14%, which is better than that of the other models, and its average checking accuracy, average recall, and average F1-Score are 0.9889, 0.9783, and 0.9834, respectively, which are 1.25%-5.16%, 4.31%-7.19%, and 3.32%, respectively, compared with that of the other three algorithms. 7.19% and 3.32%-6.76%, respectively. This paper is of great practical significance for the construction and optimization of a big data information security protection system in an industrial Internet environment. © 2024 Rongcui Na, published by Sciendo.