Ontology driven AI and Access Control Systems for Smart Fisheries

Sai Sree Laya Chukkapalli, S. Aziz, Nouran Alotaibi, Sudip Mittal, Maanak Gupta, Mahmoud Abdelsalam
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引用次数: 10

Abstract

Increasing number of internet connected devices has paved a path for smarter ecosystems in various sectors such as agriculture, aquaculture, manufacturing, healthcare, etc. Especially, integrating technologies like big data, artificial intelligence (AI), blockchain, etc. with internet connected devices has increased efficiency and productivity. Therefore, fishery farmers have started adopting smart fisheries technologies to better manage their fish farms. Despite their technological advancements smart fisheries are exposed and vulnerable to cyber-attacks that would cause a negative impact on the ecosystem both physically and economically. Therefore in this paper, we present a smart fisheries ecosystem where the architecture describes various interactions that happen between internet connected devices. We develop a smart fisheries ontology based on the architecture and implement Attribute Based Access Control System (ABAC) where access to resources of smart fisheries is granted by evaluating the requests. We also discuss how access control decisions are made in multiple use case scenarios of a smart fisheries ecosystem. Furthermore, we elaborate on some AI applications that would enhance the smart fisheries ecosystem.
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面向智能渔业的本体驱动AI和访问控制系统
越来越多的互联网连接设备为农业、水产养殖、制造业、医疗保健等各个领域的智能生态系统铺平了道路。特别是,将大数据、人工智能(AI)、区块链等技术与互联网连接设备相结合,提高了效率和生产力。因此,渔民已经开始采用智能渔业技术来更好地管理他们的养鱼场。尽管技术进步,智能渔业仍然容易受到网络攻击,这将对生态系统造成物理和经济上的负面影响。因此,在本文中,我们提出了一个智能渔业生态系统,其中架构描述了互联网连接设备之间发生的各种交互。在此基础上开发了智能渔业本体,并实现了基于属性的访问控制系统(ABAC),通过对请求的评估来授予对智能渔业资源的访问权限。我们还讨论了如何在智能渔业生态系统的多个用例场景中做出访问控制决策。此外,我们还详细介绍了一些可以增强智能渔业生态系统的人工智能应用。
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