Reliable and secure data transfer in IoT networks

Gochhayat, Sarada Prasad; Lal, Chhagan; Sharma, Lokesh; Sharma, Divya; Gupta, Deepak; Marmolejo-Saucedo, José Antonio; Köse, Utku

doi:10.1007/s11276-019-02036-0

Cited by 32 publications

(14 citation statements)

References 20 publications

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“…IoT frameworks are intensely used in many applications as demonstrated below. Figure 2 outlines some of the fundamental areas and applications of IoT which includes smart traffic system, smart environment, smart healthcare, smart home, smart agriculture, smart office, and supply chains logistics IoT [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Cloud-Based Fault Prediction Using IoT in Office Automation for Improvisation of Health of Employees

Uppal

Gupta

Juneja

et al. 2021

Journal of Healthcare Engineering

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The novel paradigm of Internet of Things (IoT) is gaining recognition in the numerous scenarios promoting the pervasive presence of smart things around us through its application in various areas of society, which includes transportation, healthcare, industries, and agriculture. One more such application is in the smart office to monitor the health of devices via machine learning (ML) that makes the equipment more efficient by allowing real-time monitoring of their health. It guarantees indoor comfort as per the user’s satisfaction as it emphasizes on fault prediction in real-life devices. Early identification of various types of faults in IoT devices is the key requirement in smart offices. IoT devices are becoming ubiquitous and provide an assistant to supervise an office that is regulated by ML and data received from sensors is stored in cloud. A recommender system facilitates the selection of an appropriate solution for faults in IoT-enabled devices to mitigate faults. The architecture proposed in this paper is used to monitor each and every office appliance connected via IoT technology using ML technique, and recommender system is used to recommend solutions for fault patterns without much human intervention. The ultrasonic motion sensor is used to fetch the information of employee availability in cubicles and data is sent to the cloud through the WiFi module. ATmega8 is used to control electrical appliances in the office environment. The significance of this work is to forecast the faults in IoT appliances which will have an impact on life and reliability of IoT appliances. The main objective is to design a prototype of a smart office using IoT that can control and automate workplace devices and forecast whether the device needs repairing or replacing, thus reducing the overall burden on the employee and helping out in increasing physical as well as mental health of the person.

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Section: Introductionmentioning

confidence: 99%

Cloud-Based Fault Prediction Using IoT in Office Automation for Improvisation of Health of Employees

Uppal

Gupta

Juneja

et al. 2021

Journal of Healthcare Engineering

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“…The alerts can be a reminder to drink water or an everyday gentle reminder that gives the user a short relief that they are not alone or anything that boosts the patient's morale. The sweat glands also have a part to play in stress monitoring [52]. Further, not only sweat but also minor changes in body fluids also specify that the person is under stress.…”

Section: Stress Monitoringmentioning

confidence: 99%

Recent Advances on IoT-Assisted Wearable Sensor Systems for Healthcare Monitoring

et al. 2021

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IoT has played an essential role in many industries over the last few decades. Recent advancements in the healthcare industry have made it possible to make healthcare accessible to more people and improve their overall health. The next step in healthcare is to integrate it with IoT-assisted wearable sensor systems seamlessly. This review rigorously discusses the various IoT architectures, different methods of data processing, transfer, and computing paradigms. It compiles various communication technologies and the devices commonly used in IoT-assisted wearable sensor systems and deals with its various applications in healthcare and their advantages to the world. A comparative analysis of all the wearable technology in healthcare is also discussed with tabulation of various research and technology. This review also analyses all the problems commonly faced in IoT-assisted wearable sensor systems and the specific issues that need to be tackled to optimize these systems in healthcare and describes the various future implementations that can be made to the architecture and the technology to improve the healthcare industry.

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“…The underlying approach is considered as an integral part of collaborations, especially in the context of IIoT sensors in CPS systems infrastructure 38 . The IIoT sensors consists of three different layers, namely, perception layer, network layer, and application layer 39,40 . The importance of the TM is not limited to a specific layer of IIoT structural design.…”

Section: Background and Related Workmentioning

confidence: 99%

DBTP2SF: A deep blockchain‐based trustworthy privacy‐preserving secured framework in industrial internet of things systems

Kumar

Tripathi

2021

Trans Emerging Tel Tech

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By providing ubiquitous connectivity, effective data analytics tools, and better decision support systems for improved market competitiveness, the industrial internet of things (IIoT) promises creative business models in different industrial domains. However, the conventional IIoT architecture can no longer provide adequate support for such an enormous device as the number of nodes, and network size increases. Therefore, several challenges, such as security, privacy, centralization, trust, and integrity prevents faster adaptation of IIoT applications. To address aforementioned challenges, we present a deep blockchain‐based trustworthy privacy‐preserving secured framework (DBTP2SF) for IIoT environment. This framework comprises of three modules, namely, trust management module, a two‐level privacy‐preservation module, and an anomaly detection module. In trustworthiness module, blockchain (BC)‐based address reputation system is proposed. In the two‐level privacy module a BC‐based enhanced proof of work technique is simultaneously applied with AutoEncoder, to transform cyber‐physical system data into a new reduced form that prevents inference and poisoning attacks. In the anomaly detection module, deep neural network is deployed. Finally, due to various limitations of current Cloud‐Fog infrastructure, we present a BC‐interplanetary file systems integrated Cloud‐Fog architecture, namely, BlockCloud and BlockFog to deploy proposed DBTP2SF framework in IIoT environment. The experiment is conducted using IIoT‐based realistic dataset, namely, ToN‐IoT. The performance analysis shows that the proposed approach outperforms using transformed dataset over peer privacy‐preserving intrusion detection strategies, and has obtained accuracy of 98.97%, and detection rate of 93.87%. Finally, we have shown the superiority of DBTP2SF framework over some of the recent state‐of‐art techniques in both non‐BC and BC‐based IIoT system.

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Reliable and secure data transfer in IoT networks

Cited by 32 publications

References 20 publications

Cloud-Based Fault Prediction Using IoT in Office Automation for Improvisation of Health of Employees

Cloud-Based Fault Prediction Using IoT in Office Automation for Improvisation of Health of Employees

Recent Advances on IoT-Assisted Wearable Sensor Systems for Healthcare Monitoring

DBTP2SF: A deep blockchain‐based trustworthy privacy‐preserving secured framework in industrial internet of things systems

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