{"title":"基于物联网的农业(Ag-IoT):架构、安全和取证的详细研究","authors":"Santoshi Rudrakar, Parag Rughani","doi":"10.1016/j.inpa.2023.09.002","DOIUrl":null,"url":null,"abstract":"<div><div>IoT based agriculture (Ag-IoT) is an emerging communication technology that is widely adopted by agricultural entrepreneurs and farmers to perform agricultural agro-chores in the farm to improve productivity, for better monitoring, and to reduce labor costs. However, the use of the Internet in Ag-IoT facilitates real-time functionality in an agriculture system, it can increase the risk of security breaches and cyber attacks that would cause the Ag-IoT system to malfunction and can affect its productivity. Ag-IoT is overlooked in cyber security parameters, which can have severe impacts on its trustworthiness and adoption by agricultural communities. To address this gap, this article presents a systematic study of the literature published between 2001 and 2023 that discusses advances in Ag-IoT technology. The subjects included in the study on Ag-IoT are emerging applications, different IoT architectures, suspected cyber attacks and cyber crimes, and challenges in incident response and digital forensics. The findings of this study encourage the reader to explore future potential research avenues related to the security risks and challenges of Ag-IoT, as well as the readiness for incident response and forensic investigation in the smart agricultural sector. The main conclusion of this study is that security must be ensured in Ag-IoT environments to offer uninterrupted services and also there is a need for forensic readiness for effective investigation in the event of unanticipated security incidents.</div></div>","PeriodicalId":53443,"journal":{"name":"Information Processing in Agriculture","volume":"11 4","pages":"Pages 524-541"},"PeriodicalIF":7.7000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"IoT based Agriculture (Ag-IoT): A detailed study on Architecture, Security and Forensics\",\"authors\":\"Santoshi Rudrakar, Parag Rughani\",\"doi\":\"10.1016/j.inpa.2023.09.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>IoT based agriculture (Ag-IoT) is an emerging communication technology that is widely adopted by agricultural entrepreneurs and farmers to perform agricultural agro-chores in the farm to improve productivity, for better monitoring, and to reduce labor costs. However, the use of the Internet in Ag-IoT facilitates real-time functionality in an agriculture system, it can increase the risk of security breaches and cyber attacks that would cause the Ag-IoT system to malfunction and can affect its productivity. Ag-IoT is overlooked in cyber security parameters, which can have severe impacts on its trustworthiness and adoption by agricultural communities. To address this gap, this article presents a systematic study of the literature published between 2001 and 2023 that discusses advances in Ag-IoT technology. The subjects included in the study on Ag-IoT are emerging applications, different IoT architectures, suspected cyber attacks and cyber crimes, and challenges in incident response and digital forensics. The findings of this study encourage the reader to explore future potential research avenues related to the security risks and challenges of Ag-IoT, as well as the readiness for incident response and forensic investigation in the smart agricultural sector. The main conclusion of this study is that security must be ensured in Ag-IoT environments to offer uninterrupted services and also there is a need for forensic readiness for effective investigation in the event of unanticipated security incidents.</div></div>\",\"PeriodicalId\":53443,\"journal\":{\"name\":\"Information Processing in Agriculture\",\"volume\":\"11 4\",\"pages\":\"Pages 524-541\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Processing in Agriculture\",\"FirstCategoryId\":\"1091\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2214317323000665\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Processing in Agriculture","FirstCategoryId":"1091","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214317323000665","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
IoT based Agriculture (Ag-IoT): A detailed study on Architecture, Security and Forensics
IoT based agriculture (Ag-IoT) is an emerging communication technology that is widely adopted by agricultural entrepreneurs and farmers to perform agricultural agro-chores in the farm to improve productivity, for better monitoring, and to reduce labor costs. However, the use of the Internet in Ag-IoT facilitates real-time functionality in an agriculture system, it can increase the risk of security breaches and cyber attacks that would cause the Ag-IoT system to malfunction and can affect its productivity. Ag-IoT is overlooked in cyber security parameters, which can have severe impacts on its trustworthiness and adoption by agricultural communities. To address this gap, this article presents a systematic study of the literature published between 2001 and 2023 that discusses advances in Ag-IoT technology. The subjects included in the study on Ag-IoT are emerging applications, different IoT architectures, suspected cyber attacks and cyber crimes, and challenges in incident response and digital forensics. The findings of this study encourage the reader to explore future potential research avenues related to the security risks and challenges of Ag-IoT, as well as the readiness for incident response and forensic investigation in the smart agricultural sector. The main conclusion of this study is that security must be ensured in Ag-IoT environments to offer uninterrupted services and also there is a need for forensic readiness for effective investigation in the event of unanticipated security incidents.
期刊介绍:
Information Processing in Agriculture (IPA) was established in 2013 and it encourages the development towards a science and technology of information processing in agriculture, through the following aims: • Promote the use of knowledge and methods from the information processing technologies in the agriculture; • Illustrate the experiences and publications of the institutes, universities and government, and also the profitable technologies on agriculture; • Provide opportunities and platform for exchanging knowledge, strategies and experiences among the researchers in information processing worldwide; • Promote and encourage interactions among agriculture Scientists, Meteorologists, Biologists (Pathologists/Entomologists) with IT Professionals and other stakeholders to develop and implement methods, techniques, tools, and issues related to information processing technology in agriculture; • Create and promote expert groups for development of agro-meteorological databases, crop and livestock modelling and applications for development of crop performance based decision support system. Topics of interest include, but are not limited to: • Smart Sensor and Wireless Sensor Network • Remote Sensing • Simulation, Optimization, Modeling and Automatic Control • Decision Support Systems, Intelligent Systems and Artificial Intelligence • Computer Vision and Image Processing • Inspection and Traceability for Food Quality • Precision Agriculture and Intelligent Instrument • The Internet of Things and Cloud Computing • Big Data and Data Mining