Security and Privacy in Solar Insecticidal Lamps Internet of Things:Requirements and Challenges

Solar insecticidal lamps(SIL) can effectively control pests and reduce the use of pesticides. Combining SIL and Internet of Things(IoT) has formed a new type of agricultural IoT,known as SIL-IoT, which can improve the effectiveness of migratory phototropic pest control. However, since the SIL is connected to the Internet, it is vulnerable to various security issues.These issues can lead to serious consequences, such as tampering with the parameters of SIL, illegally starting and stopping SIL,etc. In this paper, we describe the overall security requirements of SIL-IoT and present an extensive survey of security and privacy solutions for SIL-IoT. We investigate the background and logical architecture of SIL-IoT, discuss SIL-IoT security scenarios, and analyze potential attacks. Starting from the security requirements of SIL-IoT we divide them into six categories, namely privacy, authentication, confidentiality, access control, availability,and integrity. Next, we describe the SIL-IoT privacy and security solutions, as well as the blockchain-based solutions. Based on the current survey, we finally discuss the challenges and future research directions of SIL-IoT.

Fighting COVID-19 and Future Pandemics With the Internet of Things:Security and Privacy Perspectives

The speed and pace of the transmission of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2;also referred to as novel Coronavirus 2019 and COVID-19)have resulted in a global pandemic,with significant health,financial,political,and other implications.There have been various attempts to manage COVID-19 and other pandemics using technologies such as Internet of Things(IoT)and 5G/6G communications.However,we also need to ensure that IoT devices used to facilitate COVID-19 monitoring and treatment(e.g.,medical IoT devices)are secured,as the compromise of such devices can have significant consequences(e.g.,life-threatening risks to COVID-19 patients).Hence,in this paper we comprehensively survey existing IoT-related solutions,potential security and privacy risks and their requirements.For example,we classify existing security and privacy solutions into five categories,namely:authentication and access control solutions,key management and cryptography solutions,blockchain-based solutions,intrusion detection systems,and privacy-preserving solutions.In each category,we identify the associated challenges.We also identify a number of recommendations to inform future research.

Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

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.

A Survey on Smart Agriculture:Development Modes,Technologies,and Security and Privacy Challenges

With the deep combination of both modern information technology and traditional agriculture,the era of agriculture 4.0,which takes the form of smart agriculture,has come.Smart agriculture provides solutions for agricultural intelligence and automation.However,information security issues cannot be ignored with the development of agriculture brought by modern information technology.In this paper,three typical development modes of smart agriculture(precision agriculture,facility agriculture,and order agriculture)are presented.Then,7 key technologies and 11 key applications are derived from the above modes.Based on the above technologies and applications,6 security and privacy countermeasures(authentication and access control,privacy-preserving,blockchain-based solutions for data integrity,cryptography and key management,physical countermeasures,and intrusion detection systems)are summarized and discussed.Moreover,the security challenges of smart agriculture are analyzed and organized into two aspects:1)agricultural production,and 2)information technology.Most current research projects have not taken agricultural equipment as potential security threats.Therefore,we did some additional experiments based on solar insecticidal lamps Internet of Things,and the results indicate that agricultural equipment has an impact on agricultural security.Finally,more technologies(5 G communication,fog computing,Internet of Everything,renewable energy management system,software defined network,virtual reality,augmented reality,and cyber security datasets for smart agriculture)are described as the future research directions of smart agriculture.

Cyber Security Intrusion Detection for Agriculture 4.0: Machine Learning-Based Solutions, Datasets,and Future Directions

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.