Publications

@article{8003467,

title = {Collaborative eHealth Meets Security: Privacy-Enhancing Patient Profile Management},

author = {Rosa Sánchez-Guerrero and Florina Almenárez-Mendoza and Daniel Díaz-Sánchez and Patricia Arias-Cabarcos and Andrés Marín-López},

url = {/download/Collaborative_eHealth_meets_Security_Privacy-Enhancing_Patient_Profile_Management.pdf

https://ieeexplore.ieee.org/document/8003467},

doi = {10.1109/JBHI.2017.2655419},

issn = {2168-2194 },

year  = {2017},

date = {2017-11-01},

urldate = {2017-11-01},

journal = {IEEE Journal of Biomedical and Health Informatics},

volume = {21},

issue = {6},

pages = {1741-1749},

abstract = {Collaborative healthcare environments offer potential benefits, including enhancing the healthcare quality delivered to patients and reducing costs. As a direct consequence, sharing of electronic health records (EHRs) among healthcare providers has experienced a noteworthy growth in the last years, since it enables physicians to remotely monitor patients' health and enables individuals to manage their own health data more easily. However, these scenarios face significant challenges regarding security and privacy of the extremely sensitive information contained in EHRs. Thus, a flexible, efficient, and standards-based solution is indispensable to guarantee selective identity information disclosure and preserve patient's privacy. We propose a privacy-aware profile management approach that empowers the patient role, enabling him to bring together various healthcare providers as well as user-generated claims into an unique credential. User profiles are represented through an adaptive Merkle Tree, for which we formalize the underlying mathematical model. Furthermore, performance of the proposed solution is empirically validated through simulation experiments.},

keywords = {EHR, emadrid2, Merkle Tree, Minimal Disclosure, privacy, Profile Management},

pubstate = {published},

tppubtype = {article}

}