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Barriers and Solutions to Farmers’ Adoption of Cybersecurity Measures

RESEARCHED AND WRITTEN BY MARGARITA FONTECHA, PHD CANDIDATE, SCHOOL OF ENVIRONMENTAL DESIGN AND RURAL DEVELOPMENT, UNIVERSITY OF GUELPH

The exchange and linking of data in the agri-food sector is increasing. However, the protection of information, not so much. How can cybersecurity be incorporated into the industry? Canada has great potential to improve.

The agriculture industry must find ways to produce more food using fewer natural resources (i.e., soil, water, and energy) within the next 20 years. How can farmers around the world meet this challenge? Technology will certainly play a large role. The agriculture and food sectors have embraced technology in the last decade as a tool to become more efficient and prepared under scenarios of climate change and biodiversity loss. In November 2021, Canada joined The Agriculture Innovation Mission for Climate (AIM4C), which aims to invest heavily in “climate-smart” agriculture within the next five years. The federal government has already announced $550 million to support the development and adoption of new technologies and more sustainable land management practices.

But what is “climate smart” agriculture and how has it transformed the agri-food system from only a food focus to data production? Climate-smart agriculture (CSA) is an integrated approach to managing landscapes—cropland, livestock, forests and fisheries—that addresses the interlinked challenges of food security and accelerating climate change. One of the pillars of CSA is the use of technology to increase productivity, enhance resilience and reduce emissions. These technologies include Smart Farming (SF), Precision Agriculture (PA), and Digital Farming (DF). DF is a combination of SF and PA.

Smart farming encompasses all farm operations. Farmers can use mobile devices such as cellphones, computers, and tablets to access real-time data about the conditions of the soil, plants, terrain, climate, weather and resource usage. As a result, farmers have the information needed to make informed decisions based on concrete data, rather than their intuition.

Precision agriculture is a technology-enabled approach to farming management that observes, measures, and analyzes the needs of individual fields and crops. It is shaped by two trends: big-data creating advanced-analytics capabilities, and robotics which can include aerial imagery, sensors and sophisticated local weather forecasts.

Digital Farming relies on using data to make more informed decisions regarding the farming practices. Data help to understand patterns (i.e., rain) which can help farmers to adapt to climate change effects and be more proactive.

Technologies currently available for farmers in Canada:

  • Sensors

  • Software

  • Connectivity

  • Location

  • Robotics

  • Data analytics

As the food supply chain expands, data is becoming more and more essential, not just to business processes, but for the entire food chain. Every year an increasing number of farmers in North America are using data to know when to plant and spray crops, when to release stored crops to market and other decisions that affect farming production. Almost half of the dairy herds in north-western Europe will be milked by robots in 2025. Robotic milking is not only milking of milk, but also of data. Robots capture almost 120 data variables per cow per day (i.e., milk yield, fat, protein, milk color, etc). In today’s world, farmers and companies have access to an immense amount of information.

Technology in the agri-food system is interconnected and depends on networked information, some of which may not be secured from cyberattacks. Potential cyberattacks could cause interruptions in the refrigeration chain or other essential infrastructure for food distribution, or a targeted disruption of a highly time-sensitive process such as harvest. Cyberattacks could cause major, long-lasting effects globally and significant economic losses. Moreover, cyberattacks in many cases can harm reputations. Therefore, data becomes appealing for cybercriminals.

There are several threats that can affect the agri-food sector, including:

Ransomware: a type of malware (malicious software). If a computer or network has been infected with ransomware, the ransomware blocks access to the system or encrypts its data. Cybercriminals demand ransom money from their victims in exchange for releasing the data. This could start from an email that one person in the company received, opened and did not have protection.

Data Breach: exposes confidential, sensitive, or protected information to an unauthorized person. The files in a data breach are viewed and/or shared without permission.

Dark market or Darknet offer illicit goods for sale. Although some products for sale are legal, illicit goods such as drugs, wildlife, stolen information, and weapons are common items in these markets.

What are the main barriers for small and medium sized farms in Ontario, Canada for adopting measures to protect their farms against cyber risks?

 

  • Cost: It is the single largest barrier. Many farms are operating with older equipment that is not compatible with newer technology and would require a substantial investment to upgrade or replace.
  • Technical challenges: Other challenges include how to use the technology, rural connectivity, and being aware traditional process at farm could be more efficient using technological approach.
    • Trust. Farmers need to be assured that their data will be protected against hackers’ attacks and that companies will follow transparent protocols regarding data ownership and management.
    • Specialized tools. There is no clear specialized “agriculture only” cybersecurity products/services or providers in the Canadian market. However, companies such as BELL or Telus provide minimum protection for emails and internet use.
      • Non-traditional stakeholders in the sector (Amazon, IBM, Microsoft, Googlel) are expanding their scope to bring solutions to the agri-food system.
  • Lack of IT Sustainability. Many softwares (i.e., Antivirus) cannot be easily updated.
  • Perception. Although the investment in smart agriculture and cyberattacks have risen over the years, farmers in North America do not perceive cybersecurity as a priority, particularly small-scale farmers.

The agri-food system is interconnected and complex. Sensors in a farm could be manipulated by an actor, allowing food products to be stored at less-than-optimal temperatures, thereby leading to a risk of bacterial contamination. If no one notices this situation, products could potentially make consumers sick, which impacts the health care system.

Provincial and federal governments have a tremendous opportunity to make the Canadian agri-food system safer and more efficient.

Suggested strategies for increasing the uptake of cybersecurity measures in the agri-food system

  • Education. From the most basic concept (i.e., data), farmers, companies, agricultural associations, and the government need to strengthen their capacity to prevent cyberattacks and protect valuable content. There are many possibilities:
    • Formal and informal education about why data matters and potential risks. Partnerships between companies, government and the farmers association might be a virtuous circle that promote capacity development.
    • The role of the extension agent with much more significant expertise in software application development, data science, and digital systems broadly.
  • Innovation. Federal and provincial governments need to maintain appropriate incentives for digital innovation and take advantage of new opportunities to be knowledge brokers and facilitators of data-sharing to foster inclusive, representative, and secure data ecosystems.
  • Regulation. Federal and provincial government need to define a transparent and common set of criteria. Farmers might be more willing to invest in new equipment and technology if the government defines a transparent, common set of criteria and standards that help ensure equipment adheres to standard practices.
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References

​Dehghantanha, A., Karimipour, H., & Azmoodeh, A. (2020). Cybersecurity in Smart Farming: Canada Market Research. Guelph: University of Guelph.

FRANKENFIELD, J. (2021, October 21). Darknet Market. Retrieved from Investopedia: https://www.investopedia.com/terms/d/darknet-market-cryptomarket.asp 

Jahn, D. M., Oemichen, W. L., Treverton, D. G., David, S. L., Rosed, M. A., Brosige, M. A., . . . B.Rimestad, B. (2019). Cyber Risk and Security Implications in Smart Agriculture and Food Systems. University of Wisconsin – Madison.

Magnin, C. (2016, August 19). Como Big Data vai revolucionar a cadeia global de alimentos. Retrieved August 14, 2022, from McKinsey Digital: https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/how-big-data-will-revolutionize-the-global-food-chain/pt-BR 

McFadden, J., Casalini, F., & Antón, J. (2022). POLICIES TO BOLSTER TRUST IN AGRICULTURALDIGITALISATION. OECD.

Poppe, K. S., Wolfert, C. V., & Verwaart, T. (2013). Information and Communication Technology as a Driver for Change in Agri-food Chains. EuroChoices, 12(1), 60-65.

Ulicny, B., Mutschler, P., Barrett, L., Bethel, G., Matson, M., Strang, T., . . . linsky, s. (2018). Threats to Precision Agriculture (2018 Public-Private Analytic Exchange Program report). Office of the Director of National Intelligence; Department of Homeland Security (DHS). Retrieved from https://www.dhs.gov/sites/default/files/publications/2018%20AEP_Threats_to_Precision_Agriculture.pdf 

World Bank. (2021, April). CLIMATE-SMART AGRICULTURE. Retrieved August 14, 2022, from https://www.worldbank.org/en/topic/climate-smart-agriculture 

Margarita Fontecha

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