Intelligent monitoring for infectious diseases with fuzzy systems and edge computing: A survey

Q Jiang, X Zhou, R Wang, W Ding, Y Chu, S Tang… - Applied Soft …, 2022 - Elsevier
Infectious diseases usually have the characteristics of rapid spread with a large impact
range. Once they break out, they will cause a large area of infection, which creates …

Efficient privacy-preserving in IoMT with blockchain and lightweight secret sharing

C Li, M Dong, X Xin, J Li, XB Chen… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Internet of Medical Things (IoMT) aggregates a series of smart medical devices and fully
uses the collected health data to improve user experience, medical resource utilization, and …

A review of privacy and security of edge computing in smart healthcare systems: issues, challenges, and research directions

A Alzu'bi, A Alomar, S Alkhaza'leh… - Tsinghua Science …, 2024 - ieeexplore.ieee.org
The healthcare industry is rapidly adapting to new computing environments and
technologies. With academics increasingly committed to developing and enhancing …

An efficient lightweight privacy-preserving mechanism for industry 4.0 based on elliptic curve cryptography

S Velliangiri, R Manoharn… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
The present trend of automation anddata interchange in industrial technology is known as
Industry 4.0. Industry 4.0 is altering its next generation of distribution networks by making …

A visually meaningful image encryption scheme based on lossless compression spiht coding

Y Yang, M Cheng, Y Ding… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the popularity of social networks and the increase of cloud platform applications,
service computing has also developed. Therefore, the protection of information even privacy …

GAIN: Decentralized privacy-preserving federated learning

C Jiang, C Xu, C Cao, K Chen - Journal of Information Security and …, 2023 - Elsevier
Federated learning enables multiple participants to cooperatively train a model, where each
participant computes gradients on its data and a coordinator aggregates gradients from …

Private and energy-efficient decision tree-based disease detection for resource-constrained medical users in mobile healthcare network

S Alex, KJ Dhanaraj, PP Deepthi - IEEE Access, 2022 - ieeexplore.ieee.org
In mobile healthcare networks (MHN), outsourced disease detection services demand the
privacy preservation of medical users and health service providers (health clouds). This …

[HTML][HTML] Privacy-preserved learning from non-iid data in fog-assisted IoT: A federated learning approach

M Abdel-Basset, H Hawash, N Moustafa… - Digital Communications …, 2022 - Elsevier
With the prevalence of the Internet of Things (IoT) systems, smart cities comprise complex
networks, including sensors, actuators, appliances, and cyber services. The complexity and …

[HTML][HTML] Integrating enhanced sparse autoencoder-based artificial neural network technique and softmax regression for medical diagnosis

SA Ebiaredoh-Mienye, E Esenogho, TG Swart - Electronics, 2020 - mdpi.com
In recent times, several machine learning models have been built to aid in the prediction of
diverse diseases and to minimize diagnostic errors made by clinicians. However, since most …

Pocket diagnosis: Secure federated learning against poisoning attack in the cloud

Z Ma, J Ma, Y Miao, X Liu, KKR Choo… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Federated learning has become prevalent in medical diagnosis due to its effectiveness in
training a federated model among multiple health institutions (ie, Data Islands (DIs)) …