This book investigates novel accurate and efficient privacy-preserving techniques and their applications in e-Healthcare services. The authors first provide an overview and a general architecture of e-Healthcare and delve into discussions on various applications within the e-Healthcare domain. Simultaneously, they analyze the privacy challenges in e-Healthcare services. Then, in Chapter 2, the authors give a comprehensive review of privacy-preserving and machine learning techniques applied in their proposed solutions. Specifically, Chapter 3 presents an efficient and privacy-preserving similar…mehr
This book investigates novel accurate and efficient privacy-preserving techniques and their applications in e-Healthcare services. The authors first provide an overview and a general architecture of e-Healthcare and delve into discussions on various applications within the e-Healthcare domain. Simultaneously, they analyze the privacy challenges in e-Healthcare services. Then, in Chapter 2, the authors give a comprehensive review of privacy-preserving and machine learning techniques applied in their proposed solutions. Specifically, Chapter 3 presents an efficient and privacy-preserving similar patient query scheme over high-dimensional and non-aligned genomic data; Chapter 4 and Chapter 5 respectively propose an accurate and privacy-preserving similar image retrieval scheme and medical pre-diagnosis scheme over dimension-related medical images and single-label medical records; Chapter 6 presents an efficient and privacy-preserving multi-disease simultaneous diagnosis scheme over medical records with multiple labels. Finally, the authors conclude the monograph and discuss future research directions of privacy-preserving e-Healthcare services in Chapter 7. Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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Autorenporträt
Dr. Dan Zhu is currently an associate professor with the School of Cybersecurity, Northwestern Polytechnical University. She received her B.Eng. degree in information security and Ph.D. degree in cyberspace security from Xidian University, China, in 2017 and 2022, respectively. Her research interests are in the areas of security and privacy in online medical services, secure similarity computing, and searchable encryption. Dr. Zhu has published 10 papers in high-reputation journals and conferences introducing IEEE TDSC, TSC, and INFOCOM. Dr. Dengguo Feng received the BS degree from Shaanxi Normal University, Xi'an, China, in 1988, and the MS and PhD degrees from Xidian University, Xi'an, China, in 1993 and 1995, respectively. He is currently a professor with the Institute of Software, Chinese Academy of Sciences, Beijing, China. He was the recipient of the China National Funds for Distinguished Young Scientists. He is the vice-chairman of the Chinese Association for Cryptologic Research and a steering committee member of the Information Technology in National High-Tech R&D Program of China. Dr. Xuemin (Sherman) Shen received the Ph.D. degree in electrical engineering from Rutgers University, New Brunswick, NJ, USA, in 1990. He is a University Professor with the Department of Electrical and Computer Engineering, University of Waterloo, Canada. His research focuses on network resource management, wireless network security, Internet of Things, 5G and beyond, and vehicular networks. Dr. Shen is a registered Professional Engineer of Ontario, Canada, an Engineering Institute of Canada Fellow, a Canadian Academy of Engineering Fellow, a Royal Society of Canada Fellow, a Chinese Academy of Engineering Foreign Member, and a Distinguished Lecturer of the IEEE Vehicular Technology Society and Communications Society. Dr. Shen received "West Lake Friendship Award" from Zhejiang Province in 2023, President's Excellence in Research from the University of Waterloo in 2022, the Canadian Award for Telecommunications Research from the Canadian Society of Information Theory (CSIT) in 2021, the R.A. Fessenden Award in 2019 from IEEE, Canada, Award of Merit from the Federation of Chinese Canadian Professionals (Ontario) in 2019, James Evans Avant Garde Award in 2018 from the IEEE Vehicular Technology Society, Joseph LoCicero Award in 2015 and Education Award in 2017 from the IEEE Communications Society (ComSoc), and Technical Recognition Award from Wireless Communications Technical Committee (2019) and AHSN Technical Committee (2013). He has also received the Excellent Graduate Supervision Award in 2006 from the University of Waterloo and the Premier's Research Excellence Award (PREA) in 2003 from the Province of Ontario, Canada. He serves/served as the General Chair for the 6G Global Conference'23, and ACM Mobihoc'15, Technical Program Committee Chair/Co-Chair for IEEE Globecom'24, 16 and 07, IEEE Infocom'14, IEEE VTC'10 Fall, and the Chair for the IEEE ComSoc Technical Committee on Wireless Communications. Dr. Shen is the President of the IEEE ComSoc. He was the Vice President for Technical & Educational Activities, Vice President for Publications, Member-at-Large on the Board of Governors, Chair of the Distinguished Lecturer Selection Committee, and Member of the IEEE Fellow Selection Committee of the ComSoc. Dr. Shen served as the Editor-in-Chief of the IEEE IoT JOURNAL, IEEE Network, and IET Communications.
Inhaltsangabe
Introduction.- An Overview of e-Healthcare.- Privacy-Preserving and Machine-Learning Techniques.- Privacy-Preserving Similar Patient Query Services over Genomic Data.- Privacy-Preserving Similarity Retrieval Services over Medical Images.- Privacy-Preserving Pre-diagnosis Services over Single-label Medical Records.- Privacy-Preserving Pre-diagnosis Services over Multi-label Medical Records.- Future Works.- Conclusion.
Introduction.- An Overview of e-Healthcare.- Privacy-Preserving and Machine-Learning Techniques.- Privacy-Preserving Similar Patient Query Services over Genomic Data.- Privacy-Preserving Similarity Retrieval Services over Medical Images.- Privacy-Preserving Pre-diagnosis Services over Single-label Medical Records.- Privacy-Preserving Pre-diagnosis Services over Multi-label Medical Records.- Future Works.- Conclusion.
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