Related references
Note: Only part of the references are listed.
Article
Computer Science, Theory & Methods
Dinh C Nguyen et al.
Summary: Recent advances in communication technologies and the Internet-of-Medical-Things (IOMT) have enabled the use of artificial intelligence (AI) in smart healthcare. Federated Learning (FL), as a distributed collaborative AI paradigm, is particularly attractive for smart healthcare due to its ability to train AI models without sharing raw data. This survey provides a comprehensive overview of the recent advances in FL, its motivations, requirements, and applications in key healthcare domains.
ACM COMPUTING SURVEYS
(2023)
Article
Computer Science, Software Engineering
Ying Zhao et al.
Summary: This article discusses the privacy protection issues of federated learning, a collaborative learning framework widely used in the Internet of Things (IoT), and the threat of poisoning attacks it faces. A defense mechanism is proposed using generative adversarial networks to generate auditing data for detecting and mitigating poisoning attacks.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Computer Science, Information Systems
Bimal Ghimire et al.
Summary: This article discusses the decentralized paradigm in the field of cybersecurity and machine learning for the emerging Internet of Things (IoT). It highlights the concept of federated cybersecurity (FC) and the application of federated learning (FL) in securing the IoT environment. The article also explores the performance issues and future research trends in this area.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Theory & Methods
Hongsheng Hu et al.
Summary: This article conducts a comprehensive survey on membership inference attacks and defenses in machine learning models. Taxonomies for attacks and defenses are provided, and their pros and cons are discussed. Several promising future research directions are pointed out based on the limitations and gaps identified. The survey serves as a reference for the research community and provides a clear description for researchers outside this domain.
ACM COMPUTING SURVEYS
(2022)
Article
Automation & Control Systems
Xiaoming Yuan et al.
Summary: The article presents a machine learning based prediction model for heart disease, which can achieve binary and multiple classification predictions, including predicting whether people are sick and the severity of the disease. The model uses the Fuzzy-GBDT algorithm and bagging to improve prediction accuracy and stability.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Automation & Control Systems
Yi Sun et al.
Summary: This article investigates how to securely access patients' records from previous case-databases while protecting patient privacy. The proposed privacy-preserving medical record searching scheme based on ElGamal Blind Signature allows patients to make self-helped medical diagnosis and intelligently obtain target searching information. The scheme greatly improves the timeliness of information acquisition and meets the high-speed information sharing requirements, while ensuring bilateral security for patient privacy and case-database privacy.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Automation & Control Systems
Mamoun Alazab et al.
Summary: This article presents the application of federated learning in enhancing cybersecurity and preventing cyberattacks in real-time scenarios. The authors conducted a comprehensive survey on various federated learning models developed by researchers for authentication, privacy, trust management, and attack detection. Real-time use cases and the adoption of federated learning for data privacy and system performance improvement are also discussed. The article concludes with prominent challenges and future directions for researchers to focus on.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Automation & Control Systems
Xiaohang Xu et al.
Summary: This article tackles the issue of medical data privacy in depression through the study of federated learning. By utilizing a multiview federated learning framework and later fusion methods, it enables federated learning across different institutions or parties, resulting in improved accuracy in depression diagnosis.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Peng Zhang et al.
Summary: Arrhythmia (ARR) is a serious condition that affects the safety of human life. Current diagnosis methods using electrocardiograms (ECGs) by experts are inefficient. In this study, a deep learning model combining a convolutional neural network (CNN) and long short-term memory (LSTM) network was used to accurately classify normal sinus intervals and ARR intervals with high accuracy, sensitivity, and specificity, demonstrating potential value in clinical applications.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Yekta Said Can et al.
Summary: IoT devices generate massive biomedical data which can be used to improve health systems with advanced machine learning algorithms. Affective computing is an emerging field for monitoring mental states using physiological signals. Privacy concerns need to be addressed before analyzing physiological signals.
ACM TRANSACTIONS ON INTERNET TECHNOLOGY
(2021)
Article
Automation & Control Systems
Cheng Guo et al.
Summary: Wearable body area network plays an important role in the current COVID-19 pandemic. The designed improved symmetric homomorphic cryptosystem and fog-based communication architecture support real-time data processing and monitoring, facilitating decision-making process based on real-time data analysis.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Hardware & Architecture
Mansour Naser Alraja et al.
Summary: The study proposes an integrated solution to assist users of IoT applications in effectively protecting their privacy, with positive feedback collected in a healthcare case study.
COMPUTERS & ELECTRICAL ENGINEERING
(2021)
Article
Computer Science, Information Systems
Runnan He et al.
Summary: A novel algorithm based on U-Net and bidirectional long short-term memory with dual channels was proposed for automatic detection of QRS complexes in ECG signals, achieving high accuracy and sensitivity on two datasets after training and testing.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Bingyan Liu et al.
Summary: This paper introduces a new concept called federated adaptation to achieve better personalization results by adjusting the trained model in a federated manner. The proposed PFA framework leverages the sparsity property of neural networks to generate privacy-preserving representations and efficiently identify clients with similar data distributions, ultimately outperforming other state-of-the-art methods while ensuring user privacy.
PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE 2021 (WWW 2021)
(2021)
Proceedings Paper
Computer Science, Information Systems
Qinnan Zhang et al.
Summary: Federated learning is a distributed machine learning framework designed to protect data privacy, but challenges such as untrusted workers and difficulties in cooperative model training may hinder its widespread adoption. Therefore, it is necessary to adopt new worker selection schemes to improve model accuracy and accelerate model convergence.
2021 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE WORKSHOPS (WCNCW)
(2021)
Article
Computer Science, Information Systems
Jie Xu et al.
Summary: With the increasing availability of healthcare data, the fragmented and private nature of these data poses challenges for generating robust results. Federated learning technology shows promise in protecting privacy and connecting disparate healthcare data sources. This survey reviews the applications and potential of federated learning in the biomedical space.
JOURNAL OF HEALTHCARE INFORMATICS RESEARCH
(2021)
Article
Computer Science, Information Systems
Rafik Hamza et al.
INFORMATION SCIENCES
(2020)
Article
Automation & Control Systems
Kehua Guo et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2020)
Article
Computer Science, Information Systems
Youyang Qu et al.
IEEE INTERNET OF THINGS JOURNAL
(2020)
Article
Computer Science, Interdisciplinary Applications
Rui Zhou et al.
INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING
(2019)
