The Security Issues in IoT - Cloud: A Review

Almolhis, Nawaf; Alashjaee, Abdullah Mujawib; Duraibi, Salahaldeen; Fahad, Alqahtani; Moussa, Ahmed Nour

doi:10.1109/cspa48992.2020.9068693

Cited by 39 publications

(14 citation statements)

References 46 publications

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“…Complex applications that require high processing speed can be stored in the cloud, and can only be called when required by the devices. This will allow them to run optimally and be efficient in data collection [132].…”

Section: The Cloud and Computing Modelsmentioning

confidence: 99%

Integrating Wireless Remote Sensing and Sensors for Monitoring Pesticide Pollution in Surface and Groundwater

Mutunga,

Sinanovic,

Harrison

2024

Sensors

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Water constitutes an indispensable resource crucial for the sustenance of humanity, as it plays an integral role in various sectors such as agriculture, industrial processes, and domestic consumption. Even though water covers 71% of the global land surface, governments have been grappling with the challenge of ensuring the provision of safe water for domestic use. A contributing factor to this situation is the persistent contamination of available water sources rendering them unfit for human consumption. A common contaminant, pesticides are not frequently tested for despite their serious effects on biodiversity. Pesticide determination in water quality assessment is a challenging task because the procedures involved in the extraction and detection are complex. This reduces their popularity in many monitoring campaigns despite their harmful effects. If the existing methods of pesticide analysis are adapted by leveraging new technologies, then information concerning their presence in water ecosystems can be exposed. Furthermore, beyond the advantages conferred by the integration of wireless sensor networks (WSNs), the Internet of Things (IoT), Machine Learning (ML), and big data analytics, a notable outcome is the attainment of a heightened degree of granularity in the information of water ecosystems. This paper discusses methods of pesticide detection in water, emphasizing the possible use of electrochemical sensors, biosensors, and paper-based sensors in wireless sensing. It also explores the application of WSNs in water, the IoT, computing models, ML, and big data analytics, and their potential for integration as technologies useful for pesticide monitoring in water.

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Section: The Cloud and Computing Modelsmentioning

confidence: 99%

Integrating Wireless Remote Sensing and Sensors for Monitoring Pesticide Pollution in Surface and Groundwater

Mutunga,

Sinanovic,

Harrison

2024

Sensors

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“…For example, in fault detection in the production process, if the machine waits for data to be transmitted to the cloud and then returns a response signal, the fault may have caused a series of severe consequences. At the same time, reliability, security and privacy considerations have also resulted in some data not being put into the cloud for analysis [31]. EC can effectively solve these problems because the calculation is done at the device terminal and is not transmitted to the cloud.…”

Section: Data Processingmentioning

confidence: 99%

Review of Human-Machine Interaction Towards Industry 5.0: Human-Centric Smart Manufacturing

Yang

Liu

et al. 2022

Volume 2: 42nd Computers and Information in Engineering Conference (CIE)

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Human-centric smart manufacturing (HCSM) is one of the essential pillars in Industry 5.0. Hence, human-machine interaction (HMI), as the centre of the research agenda for the advances of smart manufacturing, has also become the focus of Industry 5.0. As Industry 5.0 proposed three core concepts of human-centric, sustainable and resilient, the design orientation of HMI needs to change accordingly. Through understanding the state-of-the-art of HMI research, the technology roadmap of HMI development in the smart manufacturing paradigm can be shaped. In this paper, the focus is to review how HMI has been applied in smart manufacturing and predict future opportunities and challenges when applying HMI to HCSM. In this paper, we provide an HMI framework based on the interaction process and analyse the existing research on HMI across four key aspects: 1) Sensor and Hardware, 2) Data Processing, 3) Transmission Mechanism, and 4) Interaction and Collaboration. We intend to analyse the current development and technologies of each aspect and their possible application in HCSM. Finally, potential challenges and opportunities in future research and applications of HMI are discussed and evaluated, especially considering that the focus of design in HCSM shifts from improving productivity to the well-being of workers and sustainability.

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“…The result is the creation of another matrix with only one row and columns equal to the number of attributes. This matrix is known as priority weights matrix [PW] as shown in (2).…”

Section: Inclusion Of Latest Hybrid Techniques Inmentioning

confidence: 99%

“…One of the greatest inventions of Gen Z, Internet has rapidly emerged over the last two decades, connecting people and organizations together into one giant family. This connectivity has generated the urgency of Internet of Things (IoT) [1], which involves sensors, software devices, and other technologies, for the purpose of maintaining the security and privacy of humongous data transmission among other devices and systems [2]. For this sole purpose, several distinct IoT platforms have come into existence with their own unique cloud service providers (CSP) at the backend.…”

Section: Introductionmentioning

confidence: 99%

A Secure IoT‐Based Cloud Platform Selection Using Entropy Distance Approach and Fuzzy Set Theory

Chakraborty

Jindal

Khosravi

et al. 2021

Wireless Communications and Mobile Computing

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With the growing emergence of the Internet connectivity in this era of Gen Z, several IoT solutions have come into existence for exchanging large scale of data securely, backed up by their own unique cloud service providers (CSPs). It has, therefore, generated the need for customers to decide the IoT cloud platform to suit their vivid and volatile demands in terms of attributes like security and privacy of data, performance efficiency, cost optimization, and other individualistic properties as per unique user. In spite of the existence of many software solutions for this decision-making problem, they have been proved to be inadequate considering the distinct attributes unique to individual user. This paper proposes a framework to represent the selection of IoT cloud platform as a MCDM problem, thereby providing a solution of optimal efficacy with a particular focus in user-specific priorities to create a unique solution for volatile user demands and agile market trends and needs using optimized distance-based approach (DBA) aided by Fuzzy Set Theory.

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The Security Issues in IoT - Cloud: A Review

Cited by 39 publications

References 46 publications

Integrating Wireless Remote Sensing and Sensors for Monitoring Pesticide Pollution in Surface and Groundwater

Integrating Wireless Remote Sensing and Sensors for Monitoring Pesticide Pollution in Surface and Groundwater

Review of Human-Machine Interaction Towards Industry 5.0: Human-Centric Smart Manufacturing

A Secure IoT‐Based Cloud Platform Selection Using Entropy Distance Approach and Fuzzy Set Theory

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