2021
DOI: 10.4018/ijssci.285593
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Security of Cloud-Based Medical Internet of Things (MIoTs)

Abstract: In this digital era expectations for medical quality have increased. As the number of patients continues to increase, conventional health care methods are having to deal with new complications. In light of these observations, researchers suggested a hybrid combination of conventional health care methods with IoT technology and develop MIoT. The goal of IoMT is to ensure that patients can respond more effectively and efficiently to their treatment. But preserving user privacy is a critical issue when it comes t… Show more

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Cited by 53 publications
(27 citation statements)
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“…It is understood that there is room for improvement in our research work. We suggest future research directions with the ideas of (i) investigating the effectiveness of the heterogeneous datasets of different disciplines to enhance the knowledge transfer between source and target models [ 40 , 41 ]; (ii) investigating the extent of smoothing, downsampling, and fine-graining of the multi-scale scheme on the performance of the model; (iii) generating additional training data using the variants of generative adversarial networks [ 42 , 43 ] because downsampling sacrifices the available ground truth data [ 44 ]; (iv) generating other types of noise such as speckle noise and random noise in the images to study the robustness of the model [ 45 , 46 ]; and (v) evaluating more noise injection approaches such as rotation, cropping, and re-sizing.…”
Section: Conclusion and Future Research Directionsmentioning
confidence: 99%
“…It is understood that there is room for improvement in our research work. We suggest future research directions with the ideas of (i) investigating the effectiveness of the heterogeneous datasets of different disciplines to enhance the knowledge transfer between source and target models [ 40 , 41 ]; (ii) investigating the extent of smoothing, downsampling, and fine-graining of the multi-scale scheme on the performance of the model; (iii) generating additional training data using the variants of generative adversarial networks [ 42 , 43 ] because downsampling sacrifices the available ground truth data [ 44 ]; (iv) generating other types of noise such as speckle noise and random noise in the images to study the robustness of the model [ 45 , 46 ]; and (v) evaluating more noise injection approaches such as rotation, cropping, and re-sizing.…”
Section: Conclusion and Future Research Directionsmentioning
confidence: 99%
“…To facilitate the optimization of the hyperparameters and examine model overfitting, k-fold cross-validation with k = 5 is adopted [ 32 , 33 , 34 ].…”
Section: Ablation Studymentioning
confidence: 99%
“…To manage the data privacy issues, often, the data is stored in an encrypted form 151,152 . To make thtis encrypted data accessible, the technique of searchable encryption comes into the picture.…”
Section: Blockchain‐based Healthcare Systemsmentioning
confidence: 99%