Future Smart Connected Communities to Fight COVID-19 Outbreak

Gupta, Deepti; Bhatt, Smriti; Gupta, Maanak; Tosun, Ali Şaman

doi:10.1016/j.iot.2020.100342

Cited by 92 publications

(41 citation statements)

References 110 publications

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“…Beside that, the number of IoT devices increased in the healthcare applications, after the evolution of COVID-19 to generate a huge amount of data, which pressures the deployed healthcare IoT network in terms of communication metrics e.g. delay, throughput, computation complexity accompanied by an erroneous diagnosis that could harmfully influence the COVID-19 disclosure and service response rate ( Gupta et al., 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Emerging IoT Applications in Sustainable Smart Cities for COVID-19: Network Security and Data Preservation Challenges with Future Directions

Adil

Khan

2021

Sustainable Cities and Society

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COVID-19 is a global infectious disease that can be easily spread by the contiguity of infected people. To prevent from COVID-19 and reduce its impact in sustainable smart cities, the global research communities are working relentlessly by harnessing the emerging technologies to develop the safest diagnosis, evaluation, and treatment procedures, and Internet of Things (IoT) is one of the pioneers among them. IoT can perform a pivotal role to diminish its immense contagious rate by suitable utilization in emerging healthcare IoT applications in sustainable smart cities. Therefore, the focus of this paper is to outline a survey of the emerging healthcare IoT applications practiced in the perspective of COVID-19 pandemic in terms of network architecture security, trustworthiness, authentication, and data preservation followed by identifying existing challenges to set the future research directions. The salient contributions of this work deal with the accomplishment of a detailed and comprehensive literature review of COVID-19 starting from 2019 through 2021 in the context of emerging healthcare IoT technology. In addition, we extend the correlated contributions of this work by highlighting the weak aspects of the existing emerging healthcare IoT applications, security of different network layers and secure communication environment followed by some associated requirements to address these challenges. Moreover, we also identify future research directions in sustainable smart cities for emerging healthcare IoT utilization in the context of COVID-19 with the most productive results and least network implementation costs.

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Section: Introductionmentioning

confidence: 99%

Emerging IoT Applications in Sustainable Smart Cities for COVID-19: Network Security and Data Preservation Challenges with Future Directions

Adil

Khan

2021

Sustainable Cities and Society

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“…Due to the innovation and convenience of cloud technology, the interest and use of cloud computing have increased among users as well as researchers. Cloud computing plays an important role in the protection of computer systems such as smart cyberphysical systems (CPSs) [7], IoT devices [8] and personal computers from several cyber-attacks, especially from malware attacks. In literature review, several studies are presented to detect malware in the cloud environment.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Behavior-Based Malware Detection System on Cloud Computing Environment

2021

Self Cite

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These days, cloud computing is one of the most promising technologies to store information and provide services online efficiently. Using this rapidly developing technology to protect computer-based systems from cyber-related attacks can bring many advantages over traditional protection schemes. The protected assets can be any computer-based systems such as cyber-physical systems (CPS), critical systems, desktop and laptop computers, mobile devices, and Internet of Things (IoT). Malicious software (malware) is any software which targets the computer-based system to launch cyber-attacks to threaten the integrity, confidentiality and availability of the data. To detect the massively growing malware attacks surface, we propose an intelligent behavior-based detection system in the cloud environment. The proposed system first creates a malware dataset on different virtual machines which identify distinctive features efficiently. Then, selected features are given to the learning-based and rule-based detection agents to separate malware from benign samples. Totally, 10,000 program samples have been analyzed to evaluate the performance of the proposed system. The proposed system can detect both known and unknown malware efficiently with high detection and accuracy rate. Besides, the proposed method results have outperformed the leading methods' results in the literature. Our evaluation results show that the proposed algorithms along with machine learning (ML) classifiers achieve 99.8% detection rate, 0.4% false positive rate, and 99.7% accuracy. Our proposed system and algorithms may assist those who would like to develop a novel malware detection system in the cloud environment.

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“…Many studies have recently concentrated on working with inflectional diseases and safely transferring them to medical centers to gain personal protection and authentication. Since the gathered data is more vulnerable and can be used by intruders to make false medical statements, authentication is also a significant factor in preventing unauthentic access [29,30]. In [31], authors suggested a dual sink solution for body area networks (DSCB) using clustering, to achieve effective and secure connectivity while still being energy efficient.…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing

et al. 2021

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Internet of Things (IoT) is a developing technology for supporting heterogeneous physical objects into smart things and improving the individuals living using wireless communication systems. Recently, many smart healthcare systems are based on the Internet of Medical Things (IoMT) to collect and analyze the data for infectious diseases, i.e., body fever, flu, COVID-19, shortness of breath, etc. with the least operation cost. However, the most important research challenges in such applications are storing the medical data on a secured cloud and make the disease diagnosis system more energy efficient. Additionally, the rapid explosion of IoMT technology has involved many cyber-criminals and continuous attempts to compromise medical devices with information loss and generating bogus certificates. Thus, the increase in modern technologies for healthcare applications based on IoMT, securing health data, and offering trusted communication against intruders is gaining much research attention. Therefore, this study aims to propose an energy-efficient IoT e-health model using artificial intelligence with homomorphic secret sharing, which aims to increase the maintainability of disease diagnosis systems and support trustworthy communication with the integration of the medical cloud. The proposed model is analyzed and proved its significance against relevant systems.

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Future Smart Connected Communities to Fight COVID-19 Outbreak

Cited by 92 publications

References 110 publications

Emerging IoT Applications in Sustainable Smart Cities for COVID-19: Network Security and Data Preservation Challenges with Future Directions

Emerging IoT Applications in Sustainable Smart Cities for COVID-19: Network Security and Data Preservation Challenges with Future Directions

Intelligent Behavior-Based Malware Detection System on Cloud Computing Environment

Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing

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