Agricultural Supply Chain Security Management Based on Distributed Blockchain and Time Series Analysis: Focus on Cross-Domain Data Security and Privacy Computing

Abstract

The agricultural supply chain is facing practical challenges such as data privacy breaches and insufficient cross domain data collaboration control in distributed scenarios. This article proposes a collaborative management mechanism that integrates distributed blockchain, time series analysis, and privacy computing to study data security in distributed agricultural supply chains. This article first elaborates on the theoretical basis of relevant technologies, with a focus on how blockchain achieves privacy isolation for cross node data transmission through asymmetric encryption technology, uses smart contracts to achieve dynamic permission control and operation tracing of distributed nodes, and adapts to the dynamic monitoring needs of distributed data streams with the real-time advantage of time series analysis; On this basis, a management mechanism covering overall architecture, node collaboration, anomaly monitoring, and cross domain data flow control was designed, and an algorithm model including data preprocessing, blockchain node feature extraction, privacy protection data processing, time series anomaly detection and analysis was constructed. Through experimental verification, accuracy, recall rate, RMSE, MAE and other indicators were evaluated using one-year operational data from a certain agricultural supply chain scenario as a sample. The results showed that the accuracy of the experimental group was 92%, the recall rate was 88%, the RMSE was 12.5, and the MAE was 9.8, all of which were better than the control group. Research has shown that this collaborative mechanism and algorithm model can effectively enhance the distributed data security protection, cross domain data flow control, and anomaly recognition capabilities of agricultural supply chains, solve the data security and privacy protection problems of agricultural supply chains in distributed scenarios, provide new methods for the safe and stable operation of agricultural supply chains, and have important engineering practical value and promotion significance.