Enhanced secure device authentication algorithm in P2P-based smart farm system

Chae, Cheol-Joo; Cho, Han-Jin

doi:10.1007/s12083-018-0635-3

Cited by 34 publications

(11 citation statements)

References 4 publications

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“…Although the system is trustworthy, it puts unnecessary computation load on resource constrained smart farm IoT devices participating in a secure P2P communication. Accordingly, authors in [78] proposed a lightweight device authentication solution in which session keys and public keys are combined to expedite the encryption/decryption tasks. It results in a fast and light-weight authentication solution which is a good fit for smart farming communication purposes.…”

Section: A Cyber Attacks Threats and Proposed Solutionsmentioning

confidence: 99%

Security and Privacy in Smart Farming: Challenges and Opportunities

et al. 2020

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Internet of Things (IoT) and smart computing technologies have revolutionized every sphere of 21 st century humans. IoT technologies and the data driven services they offer were beyond imagination just a decade ago. Now, they surround us and influence a variety of domains such as automobile, smart home, healthcare, etc. In particular, the Agriculture and Farming industries have also embraced this technological intervention. Smart devices are widely used by a range of people from farmers to entrepreneurs. These technologies are used in a variety of ways, from finding real-time status of crops and soil moisture content to deploying drones to assist with tasks such as applying pesticide spray. However, the use of IoT and smart communication technologies introduce a vast exposure to cybersecurity threats and vulnerabilities in smart farming environments. Such cyber attacks have the potential to disrupt the economies of countries that are widely dependent on agriculture. In this paper, we present a holistic study on security and privacy in a smart farming ecosystem. The paper outlines a multi layered architecture relevant to the precision agriculture domain and discusses the security and privacy issues in this dynamic and distributed cyber physical environment. Further more, the paper elaborates on potential cyber attack scenarios and highlights open research challenges and future directions. INDEX TERMS Security, privacy, smart farming, precision agriculture, cloud computing, edge computing, cyber physical systems, IoT, artificial intelligence (AI), machine learning, layered architecture.

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Section: A Cyber Attacks Threats and Proposed Solutionsmentioning

confidence: 99%

Security and Privacy in Smart Farming: Challenges and Opportunities

et al. 2020

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“…In CRNs, the transmission delay time is affected by many factors such as the data transmission time, spectrum sensing time, and presence of PU over its channels. In contrary, such factors may also affect the network security, as a malicious node can emulate a PU in order to lower the network performance [24][25].…”

Section: Related Workmentioning

confidence: 99%

Towards Securing Routing Based on Nodes Behavior During Spectrum Sensing in Cognitive Radio Networks

2020

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Routing is a challenge in cognitive radio networks (CRNs) due to the properties of cognitive radio (CR) technology, as well as other limitations. Firstly, the CR's frequency band is considered a dynamic spectrum. Therefore, since the routing algorithms used in other types of networks rely on a fixed frequency band, they cannot be directly used in CRNs. Secondly, the dynamic spectrum access, which is enabled by CR technology, negatively affects the network performance. Thirdly, having an effective routing in CRNs needs a local and continual knowledge of its changeable environment. Lastly, the presence of adversary nodes and their malicious activities affect the route establishment process, thereby reducing the network performance. This paper addresses these limitations by combining the spectrum sensing and the spectrum management phases by proposing a novel and secure routing algorithm. Security in the proposed algorithm combines two aspects. The first aspect is measuring the nodes' behavior during the spectrum sensing phase through a parameter called belief level (BL), which refers to the nodes' reliability to correctly find and use the white spectrum channels. The second aspect is securing the routing request and reply messages by encoding them with the existing cryptography techniques. The main goal of the proposed approach is to make the available paths between any two communicating nodes secure, reduce the negative effects to the licensed users over the spectrum channels, and moderate the total cost of the used channels over the best path(s). The performance evaluation in terms of end-to-end delay, packet delivery ratio, packet loss ratio, and routing overhead show that the proposed approach outperforms multiple existing routing algorithms. Moreover, the proposed algorithm is validated and verified in terms of security functionality against any attacks.

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“…The diversified geographical pattern of Nepal with diversified topography, temperature ranging from 4-40°C, and rainfall ranging from 250mm to 6000mm create enough potential for crop production which can be intensified by using precision agriculture. Despite several strengths and opportunities, PA encompasses some threats that attack the agricultural sector (Chae and Cho, 2018) as PA is connected online permanently and is a mechanical intensive industry. PA technology may not be fully accepted among the farmers.…”

Section: Swot (Strengths Weakness Opportunities Threat) Analysis Omentioning

confidence: 99%

Future prospects of precision agriculture in Nepal

Shrestha

Khanal

2020

Arch. Agric. Environ. Sci.

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Precision agriculture is a management system based on information and technology which analyses the spatial and temporal variability within the field and addresses them systematically for optimizing productivity, profitability, and environmental sustainability. It is an emerging concept of agriculture that implies a precise application of inputs at the right place, at the right time, and in the right amount to minimize the production cost, to boost profitability and reduce risks. The three main elements of precision agriculture are data and information, technology, and decision support systems. This system of management is known as ‘Site-specific management’ which makes use of technologies like global positioning system, global information system, remote sensors, yield monitors, guidance technology, variable-rate technology, hardware, and software. Agriculture is the mainstay of Nepal but still is not proficient enough to appease the daily consumption needs. The ongoing system of farming practices in Nepal is deemed insufficient to explore the available resources in its optimum potential. Many cultivable lands in the country are still a virgin, and many indigenous crop varieties have remained unexplored in their wilderness that is rich in biodiversity. These possibilities embark great room for increasing agricultural productivity through the precision farming system if adopted the technology on a large scale within the country. The national economy can be flustered and the environment can also be conserved using precision agriculture. It can address all agricultural and environmental issues. It is a technically sophisticated system and requires great technical knowledge for successful adoption and implementation. This study examines the history, global scenario, scope of precision agriculture, and its importance, opportunities, threats, and challenges in Nepal.

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Enhanced secure device authentication algorithm in P2P-based smart farm system

Cited by 34 publications

References 4 publications

Security and Privacy in Smart Farming: Challenges and Opportunities

Security and Privacy in Smart Farming: Challenges and Opportunities

Towards Securing Routing Based on Nodes Behavior During Spectrum Sensing in Cognitive Radio Networks

Future prospects of precision agriculture in Nepal

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