So-Hyeon Cho Dong-Seok Kang Min-Song Kang Hyeon-Soo Kim Jin-Woong Bae Chung-Il Lee Han-Byeol Ji Yo-Han Won Hyeon-Kyoung Hong Kyounggon Kim https://orcid.org/0000-0002-5675-4253


In the era of agriculture 4.0, cutting-edge technologies including Information and communication technology (ICT) is being introduced into traditional agriculture. As farm intelligence emerges as a key area of smart agriculture, the scope of agriculture has expanded from the seed industry to distribution and logistics, however the area that is still most directly connected to the physical agricultural environment is smart farming. Cybersecurity incidents or cybercrimes in smart farming can directly damage crops and harm human safety. Research on individual technical elements that constitute smart farming has been ongoing for a long time relatively, however it has not been long since the work of systematically identifying and classifying threats to smart agriculture as a whole. In this study, STRIDE threat modeling is used to identify cyber threats to greenhouse and make system design more robust. Through this work, we have derived 126 threats and have created 4 types of attack trees. It will be the basis to allow systematic threat classification more clearly in smart greenhouse.


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