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.
