The interoperability of services and the sharing of health data have been a continuous goal for health professionals, patients, institutions, and policy makers. However, several issues have been hindering this goal, such as incompatible implementations of standards (e.g., HL7, DICOM), multiple ontologies, and security constraints. Cross-enterprise document sharing (XDS) workflows were proposed by Integrating the Healthcare Enterprise (IHE) to address current limitations in exchanging clinical data among organizations. To ensure data protection, XDS actors must be placed in trustworthy domains, which are normally inside such institutions. However, due to rapidly growing IT requirements, the outsourcing of resources in the Cloud is becoming very appealing. This paper presents a software proxy that enables the outsourcing of XDS architectural parts while preserving the interoperability, confidentiality, and searchability of clinical information. A key component in our architecture is a new searchable encryption (SE) scheme-Posterior Playfair Searchable Encryption (PPSE)-which, besides keeping the same confidentiality levels of the stored data, hides the search patterns to the adversary, bringing improvements when compared to the remaining practical state-of-the-art SE schemes.
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http://dx.doi.org/10.1109/JBHI.2013.2292776 | DOI Listing |
Data Brief
February 2025
Faculty of Business, Economics and Social Sciences, University of Hohenheim, Stuttgart, Germany.
The MaschinenBauIndustrie Knowledge Graph (MBI-KG) is a structured and semantically enriched dataset extracted from the 1937 publication "Die Maschinen-Industrie im Deutschen Reich" (The Machinery Industry in the German Reich), published by the "Wirtschaftsgruppe Maschinenbau" and edited by Herbert Patschan. This historical source offers data on German companies within the mechanical engineering industry during the pre-World War II era. The book was digitized, and Optical Character Recognition (OCR) was applied to extract text.
View Article and Find Full Text PDFEntropy (Basel)
November 2024
Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, SI-2000 Maribor, Slovenia.
After a boom that coincided with the advent of the internet, digital cameras, digital video and audio storage and playback devices, the research on data compression has rested on its laurels for a quarter of a century. Domain-dependent lossy algorithms of the time, such as JPEG, AVC, MP3 and others, achieved remarkable compression ratios and encoding and decoding speeds with acceptable data quality, which has kept them in common use to this day. However, recent computing paradigms such as cloud computing, edge computing, the Internet of Things (IoT), and digital preservation have gradually posed new challenges, and, as a consequence, development trends in data compression are focusing on concepts that were not previously in the spotlight.
View Article and Find Full Text PDFHealthcare (Basel)
December 2024
Department of Precision Medicine, Sungkyunkwan University School of Medicine, Suwon 16419, Republic of Korea.
Federated learning (FL) is revolutionizing healthcare by enabling collaborative machine learning across institutions while preserving patient privacy and meeting regulatory standards. This review delves into FL's applications within smart health systems, particularly its integration with IoT devices, wearables, and remote monitoring, which empower real-time, decentralized data processing for predictive analytics and personalized care. It addresses key challenges, including security risks like adversarial attacks, data poisoning, and model inversion.
View Article and Find Full Text PDFJ Biomed Semantics
December 2024
Medical BioSciences Department, Radboud University Medical Center, Nijmegen, The Netherlands.
Motivation: We are witnessing an enormous growth in the amount of molecular profiling (-omics) data. The integration of multi-omics data is challenging. Moreover, human multi-omics data may be privacy-sensitive and can be misused to de-anonymize and (re-)identify individuals.
View Article and Find Full Text PDFBiodivers Data J
December 2024
Universidad Nacional Autonoma de Mexico, Mexico, Mexico Universidad Nacional Autonoma de Mexico Mexico Mexico.
Background: The coastal habitats in the southern Gulf of Mexico face multiple threats, such as rising water temperatures, acidification, increased turbidity, invasive species and pollutants. This imperils the biodiversity of beaches, wetlands and coral reefs. To address this, there is a need for comprehensive baseline information on marine biodiversity.
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