在当前信息化高速发展的背景下，智慧农业作为农业发展的必然趋势，其中农业大数据是实现智慧农业的重要支撑。尽管农业大数据带来了巨大的产业动能，但也伴随诸多的数据安全问题，有效处理农业大数据技术与数据安全的关系显得至关重要。首先综合分析当前各种观点重新定义了农业大数据，然后通过案例详述了其在农业供应链各环节中的促进作用，接着深入剖析了农业大数据的泛在性、社会性、交叉性等专有特征。最后，基于安全三项基本要素（机密性、完整性和可用性）以及农业大数据的专有特征，从数据采集、数据传输、数据存储等大数据生命周期的七个阶段出发，构建了智慧农业场景下的大数据安全风险框架。从大数据存在的共性问题引出农业领域下基于专有特征的特性问题，并结合实际智慧农业场景，提出了有针对性的安全解决策略。本文将对未来研究智慧农业领域中数据安全问题的解决方案提供新思路，旨在促进智慧农业更快更安全发展。

In the context of the rapid development of informatization, intelligent agriculture is an inevitable trend in agricultural development, and agricultural big data plays an important role in the realization of intelligent agriculture. Although agricultural big data has brought huge industrial momentum, many data security-related issues arose. It is crucial to handle the relationship between agricultural big data technology and data security effectively. First and foremost, this paper redefined the agricultural big data by analyzing various perspectives comprehensively, and elaborated on its promotion role in each aspect of the agricultural supply chain through a case study. Furthermore, it conducted an in-depth analysis on the distinctive attributes of agricultural big data, including its ubiquity, sociality, intersectionality, and more. Lastly, based on three fundamental elements of security (confidentiality, integrity and availability), three key functions of security (authentication, authorization and audit) and proprietary characteristics of agricultural big data, from the perspective of the seven-stage life cycle of the big data (data collection, data transmission, data storage, etc.), we proceed to construct a comprehensive framework for managing big data security risks in intelligent agriculture scenarios. The unique features of agriculture present particular obstacles within the broader context of big data. To address this issue, a customized solution has been devised, taking into account the specific needs and requirements of intelligent farming practices. This paper will introduce fresh insights and perspectives to address future data security issues in the field of intelligent agriculture, aiming to promote faster and safer development of intelligent agriculture.