农业机械学报2025，Vol.56Issue(10)：184-199,276,17.DOI:10.6041/j.issn.1000-1298.2025.10.019
农业大数据与隐私计算技术研究综述
Review on Agricultural Big Data and Privacy Computing Technology
摘要
Abstract
In recent years,with the rapid development of sensors,remote sensing,and Internet technologies,agricultural big data has shown explosive growth.The traditional centralized processing methods integrated multi-party agricultural data for crop growth evaluation and yield prediction.However,these methods face great challenges with privacy leakage and low sharing efficiency in the process of data transmission.Moreover,multi-party data also faces data security issues such as data copyright protection.To address the above problems,privacy computing,an emerging data security technology,provides a feasible path to achieve multi-party collaborative analysis without disclosing the original data.Firstly,the landscape of agricultural big data was comprehensively reviewed from data acquisition,preprocessing,storage,and analysis to its key applications in precision farming,yield forecasting,pest monitoring,supply chain traceability,and agricultural finance.Then the principles and applicable scenarios of mainstream privacy computing technologies such as homomorphic encryption,secure multi-party computation,differential privacy,and federated learning were systematically summarized.To emphatically analyze the applications of privacy computing technology in the agricultural field,the advanced research of privacy computing was outlined in agricultural data transmission,pest and disease detection,crop monitoring,and yield prediction.Meanwhile,existing key challenges of the current privacy computing technology were summarized,including communication cost,computational complexity,heterogeneous adaptability,evaluation mechanism,and the trade-off between privacy protection and model performance.Finally,future directions of privacy computing technologies on communication compression,lightweight encryption,multimodal modeling,construction of evaluation systems,and privacy-performance optimization were explored to facilitate the intelligent development of agriculture.关键词
农业大数据/智慧农业/隐私计算/数据安全Key words
agricultural big data/smart agriculture/privacy computing/data security分类
农业工程引用本文复制引用
吴政娴,文娟..农业大数据与隐私计算技术研究综述[J].农业机械学报,2025,56(10):184-199,276,17.基金项目
国家重点研发计划项目(2021QY2221-1) （2021QY2221-1）
