In recent years, Smart Farming (SF) and Precision Agriculture (PA) have attracted attention from both the agriculture industry as well as the research community. Altogether, SF and PA aim to help farmers use inputs (such as fertilizers and pesticides) more efficiently through using Internet of Things (IoT) devices, but in doing so, they create new security threats that can defeat this purpose in the absence of adequate awareness and proper countermeasures. A survey on different security-related challenges is required to raise awareness and pave they way for further research in this area. In this paper, we first itemize the security aspects of SF and PA. Next, we review the types of cyber attacks that can violate each of these aspects. Accordingly, we present a taxonomy on cyber-threats to SF and PA on the basis of their relations to different stages of Cyber-Kill Chain (CKC). Among cyber-threats, we choose Advanced Persistent Threats (APTs) for further study. Finally, we studied related risk mitigation strategies and countermeasure, and developed a future road map for further study in this area. This paper’s main contribution is a categorization of security threats within the SF/PA areas and provide a taxonomy of security threats for SF environments so that we may detect the behavior of APT attacks and any other security threat in SF and PA environments.

Smart farming aims to improve farming using modern technologies and smart devices. Smart devices help farmers to collect and analyze data regarding different aspects of their business. These data are utilized by various stakeholders, including farmers, technology providers, supply chain investigators, and agricultural service providers. These data sources can be considered big data due to their volume, velocity, and variety. The wide use of data collection and communication technologies has increased concerns about the privacy of farmers and their data. Although some previous studies have reviewed the security aspects of smart farming, the privacy challenges and solutions are not sufficiently explored in the literature. In this paper, we present a holistic review of big data privacy in smart farming. The paper utilizes a data lifecycle schema and describes privacy concerns and requirements in smart farming in each of the phases of this data lifecycle. Moreover, it provides a comprehensive review of the existing solutions and the state-of-the-art technologies that can enhance data privacy in smart farming.

Reed, M. S., K. Hubacek, A. Bonn, T. P. Burt, J. Holden, L. C. Stringer, N. Beharry-Borg, S. Buckmaster, D. Chapman, P. J. Chapman, G. D. Clay, S. J. Cornell, A. J. Dougill, A. C. Evely, E. D. G. Fraser, N. Jin, B. J. Irvine, M. J. Kirkby, W. E. Kunin, C. Prell, C. H. Quinn, B. Slee, S. Stagl, M. Termansen, S. Thorp, and F. Worrall. 2013. Anticipating and managing future trade-offs and complementarities between ecosystem services. Ecology and Society 18(1): 5. https://doi.org/10.5751/ES-04924-180105

Approximately one third of the world’s food is lost, and reducing this represents an important strategy for promoting more sustainable food systems and addressing global food insecurity. This paper presents a preliminary assessment of the socio-economic factors that are significant in causing food loss in developing countries. These countries were chosen because the majority of food waste in poorer nations happens on or around the farm and is due to inefficient storage and processing facilities (by contrast, the majority of food waste in the global north is caused by consumers or retailers and, hence, is a very different problem). To explore this topic, we conducted a multivariate panel data analysis where the volume of food loss in 93 countries over 20 years was used as the dependent variable and a range of socio-economic factors were used as independent variables. Results show that, for the countries in the global south, variables related to wealth, agricultural machinery, transportation, and telecommunications were significant in explaining the amount of lost food. We used these results to model the effectiveness of different hypothetical policies designed to reduce food loss and estimate that up to 49% of food loss could be averted by improving each countries’ performance on these variables. While these results seem to offer huge opportunities to improve the sustainability of global agricultural systems and address global food security, this paper concludes on a note of caution: as countries grow wealthy enough to address the food lost by challenges associated with on-farm issues, these same countries may start to experience more food waste at the consumer/retailer end of the food chain. Therefore, any attempt to reduce on-farm food loss in lower income countries must be met with policies to reduce the emerging problems of food waste amongst consumers and retailers.