An efficient approach for enhancing security in Internet of Things using the optimum authentication key

Kalyani, G.; Chaudhari, Shilpa

doi:10.1080/1206212x.2019.1619277

Cited by 30 publications

(19 citation statements)

References 26 publications

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“…The increase in the number of devices, applications, and parties increases the risk of data compromise. Integrity ensures the health data offered to any entity or captured via a system are consistent and accurate through the intended information and not modified in any method [ 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 ]. E-health cloud requires high reliability.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluating the E-Health Cloud Computing Systems Adoption in Taiwan’s Healthcare Industry

Chang

Pan

et al. 2021

Life

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Although the electronic health (e-health) cloud computing system is a promising innovation, its adoption in the healthcare industry has been slow. This study investigated the adoption of e-health cloud computing systems in the healthcare industry and considered security functions, management, cloud service delivery, and cloud software for e-health cloud computing systems. Although numerous studies have determined factors affecting e-health cloud computing systems, few comprehensive reviews of factors and their relations have been conducted. Therefore, this study investigated the relations between the factors affecting e-health cloud computing systems by using a multiple criteria decision-making technique, in which decision-making trial and evaluation laboratory (DEMATEL), DANP (DEMATEL-based Analytic Network Process), and modified VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) approaches were combined. The intended level of adoption of an e-health cloud computing system could be determined by using the proposed approach. The results of a case study performed on the Taiwanese healthcare industry indicated that the cloud management function must be primarily enhanced and that cost effectiveness is the most significant factor in the adoption of e-health cloud computing. This result is valuable for allocating resources to decrease performance gaps in the Taiwanese healthcare industry.

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Section: Literature Reviewmentioning

confidence: 99%

Evaluating the E-Health Cloud Computing Systems Adoption in Taiwan’s Healthcare Industry

Chang

Pan

et al. 2021

Life

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“…e combination of variation with selection and crossover ensures the effectiveness of the genetic algorithm and improves the search efficiency of the algorithm. e current early-warning methods of finance companies are too old, the financial information used in univariate early warning is rather one-sided, and the accuracy of earlywarning results is not high [20][21][22][23][24]. First of all, univariate early warning is not combined with a certain theoretical basis, it mainly relies on the subjective judgment of finance personnel in selecting indicators and risk evaluation, and there is also a problem of poor consideration for the comprehensiveness of the selected indicators, which will lead to the lack of credibility of the early-warning results.…”

Section: Financing Risk Investment Riskmentioning

confidence: 99%

Risk Prediction and Response Strategies in Corporate Financial Management Based on Optimized BP Neural Network

Zhai¹

2021

Complexity

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This paper mainly analyzes the theories related to the financial risk of the company and combines the principles of principal component analysis, particle swarm optimization algorithm, and artificial neural network to derive the financial risk index system of the company. To improve the accuracy of financial risk prediction, principal component analysis and particle swarm algorithm are applied to optimize the BP neural network model, the input data of the prediction model is improved, and the optimal initial weights and thresholds are given to the BP neural network by using particle swarm algorithm search, whereby the financial risk prediction model of particle swarm optimization BP neural network is constructed. The empirical results show that the model constructed by BP neural network not only has a high accuracy rate for static financial risk evaluation but also has a better prediction effect. After training and testing, the BP neural network-based enterprise financial risk evaluation model can accurately determine the existing financial situation of enterprise financial management and has a good prediction effect. Our research method is a fusion of the processing of the two methods, which belongs to the first integration of results.

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“…Other related research has been dedicated to the authentication architecture used to secure IoT-based cloud computing systems used for smart innovation, technology development, environment simulations and various educational applications [44,47,48]. In addition, Kalyani and Chaudhari [56] presented an efficient approach for enhancing security in IoT-based by using the optimum authentication key. The enhances IoT security authentication by utilizing cryptographic-based methodologies to secure IoT sensitive data with the help of optima homomorphic encryption with high dependability.…”

Section: Security Requirements For Iot-cloud-based E-health Systemsmentioning

confidence: 99%

Security and Privacy in IoT-Cloud-Based e-Health Systems—A Comprehensive Review

2020

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When the Internet and other interconnected networks are used in a health system, it is referred to as “e-Health.” In this paper, we examined research studies from 2017–2020 to explore the utilization of intelligent techniques in health and its evolution over time, particularly the integration of Internet of Things (IoT) devices and cloud computing. E-Health is defined as “the ability to seek, find, understand and appraise health information derived from electronic sources and acquired knowledge to properly solve or treat health problems. As a repository for health information as well as e-Health analysis, the Internet has the potential to protect consumers from harm and empower them to participate fully in informed health-related decision-making. Most importantly, high levels of e-Health integration mitigate the risk of encountering unreliable information on the Internet. Various research perspectives related to security and privacy within IoT-cloud-based e-Health systems are examined, with an emphasis on the opportunities, benefits and challenges of the implementation such systems. The combination of IoT-based e-Health systems integrated with intelligent systems such as cloud computing that provide smart objectives and applications is a promising future trend.

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An efficient approach for enhancing security in Internet of Things using the optimum authentication key

Cited by 30 publications

References 26 publications

Evaluating the E-Health Cloud Computing Systems Adoption in Taiwan’s Healthcare Industry

Evaluating the E-Health Cloud Computing Systems Adoption in Taiwan’s Healthcare Industry

Risk Prediction and Response Strategies in Corporate Financial Management Based on Optimized BP Neural Network

Security and Privacy in IoT-Cloud-Based e-Health Systems—A Comprehensive Review

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