A Enhancing Cybersecurity Resilience for Low-Income Farmers in Developing Nations: A Fuzzy Cognitive Mapping Approach

Rural farmers with limited resources in developing nations who integrate technology into their sustainable agricultural practices encounter a range of obstacles, including cybersecurity vulnerabilities, insufficient familiarity with technology, restricted finances, and a lack of financial backing. Ensuring the security of these sustainable farming initiatives becomes imperative to ensure the advancement of sustainability, resilience, and human-centered approaches in agriculture. This, in turn, supports objectives such as food security and poverty alleviation in these developing regions. Unfortunately, the absence of suitable and tailored methods for assessing cybersecurity risks in low-income farming exacerbates this situation. This research article introduces a streamlined approach for evaluating cybersecurity risks that specifically addresses the needs of low-income farmers in developing countries. The proposed methodology leverages Fuzzy Cognitive Mapping and asset-focused assessments to quantify potential risks. To validate its effectiveness, the methodology was applied to a real-world case study: the “Ferme-Ecole” project in Tsevie, Togo. The findings reveal that the “Ferme-Ecole” project faces elevated risks in areas involving human interactions. Overall, the proposed approach proves to be effective, adaptable, and cost-efficient, offering immediate insights and rationale for the efficacy of implemented cybersecurity measures.