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• Cybersecurity Challenges in Agricultural Digitalization: A Systematic Review with Python-Based Analysis

  33-47

  Zsanett Porkoláb-Angyalos

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  284

  The intersection of agriculture and cybersecurity has become a prominent research focus in recent years, driven by the rapid adoption of IoT (Internet of Things) and precision farming technologies. These technological innovations have revolutionized agricultural processes, enhancing efficiency and sustainability while introducing significant security risks. This study conducts a systematic literature review (SLR) to address key cybersecurity issues in agriculture, with a particular emphasis on IoT vulnerabilities and threats. Using Python-based text analysis techniques, the research automated the analysis of abstracts and full texts, enabling rapid filtering and thematic categorization of relevant studies. From an initial pool of 1,039 publications, 40 relevant studies were identified based on rigorous screening criteria. The thematic analysis revealed that 44.9% of the publications focus on IoT device vulnerabilities, 32.7% on agricultural cybersecurity challenges, and 22.4% on the security issues of Agriculture 4.0 and precision farming. Methodological analysis indicated that machine learning, simulation models, and case studies dominate the research landscape, while surveys and experimental studies appear less frequently. The findings highlight the critical importance of developing robust cybersecurity strategies and technologies in the agricultural sector, particularly to mitigate the risks posed by IoT devices.