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您的检索式：作者名="Othmane Friha"
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| 1 | Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies显示文摘This paper presents a comprehensive review of emerging technologies for the internet of things(IoT)-based smart agriculture.We begin by summarizing the existing surveys and describing emergent technologies for the agricultural IoT,such as unmanned aerial vehicles,wireless technologies,open-source IoT platforms,software defined networking(SDN),network function virtualization(NFV)technologies,cloud/fog computing,and middleware platforms.We also provide a classification of IoT applications for smart agriculture into seven categories:including smart monitoring,smart water management,agrochemicals applications,disease management,smart harvesting,supply chain management,and smart agricultural practices.Moreover,we provide a taxonomy and a side-by-side comparison of the state-ofthe-art methods toward supply chain management based on the blockchain technology for agricultural IoTs.Furthermore,we present real projects that use most of the aforementioned technologies,which demonstrate their great performance in the field of smart agriculture.Finally,we highlight open research challenges and discuss possible future research directions for agricultural IoTs. | Othmane Friha Mohamed Amine Ferrag Lei Shu Leandros Maglaras Xiaochan Wang | 2021 | IEEE/CAA Journal of Automatica Sinica2021，8，4： | 15 |
| 2 | Cyber Security Intrusion Detection for Agriculture 4.0: Machine Learning-Based Solutions, Datasets,and Future Directions显示文摘In this paper,we review and analyze intrusion detection systems for Agriculture 4.0 cyber security.Specifically,we present cyber security threats and evaluation metrics used in the performance evaluation of an intrusion detection system for Agriculture 4.0.Then,we evaluate intrusion detection systems according to emerging technologies,including,Cloud computing,Fog/Edge computing,Network virtualization,Autonomous tractors,Drones,Internet of Things,Industrial agriculture,and Smart Grids.Based on the machine learning technique used,we provide a comprehensive classification of intrusion detection systems in each emerging technology.Furthermore,we present public datasets,and the implementation frameworks applied in the performance evaluation of intrusion detection systems for Agriculture 4.0.Finally,we outline challenges and future research directions in cyber security intrusion detection for Agriculture 4.0. | Mohamed Amine Ferrag Lei Shu Othmane Friha Xing Yang | 2022 | IEEE/CAA Journal of Automatica Sinica2022，9，3： | 0 |
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