Secure and Efficient Multi-Party Directory Publication for Privacy-Preserving Data Sharing

2018 ◽  
pp. 71-94
Author(s):  
Katchaguy Areekijseree ◽  
Yuzhe Tang ◽  
Ju Chen ◽  
Shuang Wang ◽  
Arun Iyengar ◽  
...  
Keyword(s):  
Data Sharing ◽  
Privacy Preserving

scholarly journals SPChain: Blockchain-based medical data sharing and privacy-preserving eHealth system

2021 ◽  
Vol 58 (4) ◽  
pp. 102604
Author(s):  
Renpeng Zou ◽  
Xixiang Lv ◽  
Jingsong Zhao
Keyword(s):  
Data Sharing ◽  
Privacy Preserving ◽  
Medical Data

Traceable and Privacy-Preserving Non-Interactive Data Sharing in Mobile Crowdsensing

2021 ◽  
Author(s):  
Fuyuan Song ◽  
Zheng Qin ◽  
Jinwen Liang ◽  
Pulei Xiong ◽  
Xiaodong Lin
Keyword(s):  
Data Sharing ◽  
Privacy Preserving ◽  
Mobile Crowdsensing ◽  
Interactive Data

scholarly journals Efficient and Privacy-Preserving Medical Data Sharing in Internet of Things With Limited Computing Power

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 28019-28027 ◽  
Author(s):  
Dong Zheng ◽  
Axin Wu ◽  
Yinghui Zhang ◽  
Qinglan Zhao
Keyword(s):  
Internet Of Things ◽  
Data Sharing ◽  
Privacy Preserving ◽  
Medical Data ◽  
Computing Power

scholarly journals Towards a Privacy-Preserving Way of Vehicle Data Sharing – A Case for Blockchain Technology?

2018 ◽  
pp. 111-122 ◽  
Author(s):  
Christian Kaiser ◽  
Marco Steger ◽  
Ali Dorri ◽  
Andreas Festl ◽  
Alexander Stocker ◽  
...  
Keyword(s):  
Data Sharing ◽  
Privacy Preserving ◽  
Blockchain Technology ◽  
Vehicle Data

An Information-Aware Privacy-Preserving Accelerometer Data Sharing

2017 ◽  
pp. 425-432 ◽  
Author(s):  
Mingming Lu ◽  
Yihan Guo ◽  
Dan Meng ◽  
Cuncai Li ◽  
Yin Zhao
Keyword(s):  
Data Sharing ◽  
Privacy Preserving ◽  
Accelerometer Data

Edge-Assisted Privacy-Preserving Raw Data Sharing Framework for Connected Autonomous Vehicles

2020 ◽  
Vol 27 (3) ◽  
pp. 24-30 ◽  
Author(s):  
Jinbo Xiong ◽  
Renwan Bi ◽  
Mingfeng Zhao ◽  
Jingda Guo ◽  
Qing Yang
Keyword(s):  
Data Sharing ◽  
Autonomous Vehicles ◽  
Privacy Preserving ◽  
Raw Data

Framework Design and Case Study for Privacy-Preserving Medical Data Publishing

2013 ◽  
Vol 4 (4) ◽  
pp. 48-65 ◽  
Author(s):  
Yu Niu ◽  
Ji-Jiang Yang ◽  
Qing Wang
Keyword(s):  
Data Sharing ◽  
Personal Information ◽  
Real Life ◽  
Privacy Preserving ◽  
Medical Data ◽  
Data Publishing ◽  
Free Text ◽  
Patient Privacy ◽  
Healthcare Data

With the pervasive using of Electronic Medical Records (EMR) and telemedicine technologies, more and more digital healthcare data are accumulated from multiple sources. As healthcare data is valuable for both commercial and scientific research, the demand of sharing healthcare data has been growing rapidly. Nevertheless, health care data normally contains a large amount of personal information, and sharing them directly would bring huge threaten to the patient privacy. This paper proposes a privacy preserving framework for medical data sharing with the view of practical application. The framework focuses on three key issues of privacy protection during the data sharing, which are privacy definition/detection, privacy policy management, and privacy preserving data publishing. A case study for Chinese Electronic Medical Record (ERM) publishing with privacy preserving is implemented based on the proposed framework. Specific Chinese free text EMR segmentation, Protected Health Information (PHI) extraction, and K-anonymity PHI anonymous algorithms are proposed in each component. The real-life data from hospitals are used to evaluate the performance of the proposed framework and system.

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