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A Study on Threat Modeling in Smart Greenhouses
Author(s) -
So-Hyeon Cho,
Dongseok Kang,
Min-Song Kang,
Hyeon Soo Kim,
Jin-Woong Bae,
Chung Il Lee,
Han-Byeol Ji,
Yo-Han Won,
Hyeon-Kyeong Hong,
Kyounggon Kim
Publication year - 2020
Publication title -
journal of information security and cybercrimes research
Language(s) - English
Resource type - Journals
eISSN - 1658-7782
pISSN - 1658-7790
DOI - 10.26735/kkjn1042
Subject(s) - agriculture , scope (computer science) , harm , work (physics) , business , computer security , computer science , information and communications technology , engineering , geography , political science , mechanical engineering , archaeology , world wide web , law , programming language
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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