A universal legal framework as a prerequisite for database interoperability.

MOTIVATION: Rare diseases affect millions of people worldwide, yet their genomic foundations remain poorly understood due to limited patient data and strict privacy regulations, such as the General Data Protection Regulation (GDPR) (https://gdpr.eu/tag/gdpr/) in March 2025. These restrictions can hinder the collaborative analysis of genomic data necessary for uncovering disease-causing variants. RESULTS: We present PRISM, a novel privacy-preserving framework based on fully homomorphic encryption (FHE) that facilitates rare disease variant analysis across multiple institutions without exposing sensitive genomic information. To address the challenges of centralized trust, PRISM is built upon a Threshold FHE scheme. This approach decentralizes key management across participating institutions and ensures no single entity can unilaterally decrypt sensitive data. Our method filters disease-causing variants under recessive, dominant, and de novo inheritance models entirely on encrypted data. We propose two algorithmic variants: a multiplication-intensive (MUL-IN) approach and an addition-intensive (ADD-IN) approach. The ADD-IN algorithms minimize the number of costly multiplication operations, enabling up to a 17× improvement in runtime for recessive/dominant filtering and 22× for de novo filtering, compared to MUL-IN methods. While ADD-IN produces larger ciphertexts, efficient parallelization via SIMD and multithreading allows it to handle millions of variants in reasonable time. To the best of our knowledge, this is the first study that utilizes FHE for privacy-preserving rare disease analysis across multiple inheritance models, demonstrating its practicality and scalability in a single-cloud setting. AVAILABILITY AND IMPLEMENTATION: The source code and the data used in this work can be found in https://github.com/mdppml/PRISM.git.

Computer Security↗

PubMed2025

Privacy-preserving framework for genomic computations via multi-key homomorphic encryption.

MOTIVATION: The affordability of genome sequencing and the widespread availability of genomic data have opened up new medical possibilities. Nevertheless, they also raise significant concerns regarding privacy due to the sensitive information they encompass. These privacy implications act as barriers to medical research and data availability. Researchers have proposed privacy-preserving techniques to address this, with cryptography-based methods showing the most promise. However, existing cryptography-based designs lack (i) interoperability, (ii) scalability, (iii) a high degree of privacy (i.e. compromise one to have the other), or (iv) multiparty analyses support (as most existing schemes process genomic information of each party individually). Overcoming these limitations is essential to unlocking the full potential of genomic data while ensuring privacy and data utility. Further research and development are needed to advance privacy-preserving techniques in genomics, focusing on achieving interoperability and scalability, preserving data utility, and enabling secure multiparty computation. RESULTS: This study aims to overcome the limitations of current cryptography-based techniques by employing a multi-key homomorphic encryption scheme. By utilizing this scheme, we have developed a comprehensive protocol capable of conducting diverse genomic analyses. Our protocol facilitates interoperability among individual genome processing and enables multiparty tests, analyses of genomic databases, and operations involving multiple databases. Consequently, our approach represents an innovative advancement in secure genomic data processing, offering enhanced protection and privacy measures. AVAILABILITY AND IMPLEMENTATION: All associated code and documentation are available at https://github.com/farahpoor/smkhe.

Computer Security↗

PubMed2004

Wireless networking for the dental office: current wireless standards and security protocols.

Digital radiography has gained immense popularity in dentistry today in spite of the early difficulty for the profession to embrace the technology. The transition from film to digital has been happening at a faster pace in the fields of Orthodontics, Oral Surgery, Endodontics, Periodontics, and other specialties where the radiographic images (periapical, bitewing, panoramic, cephalometric, and skull radiographs) are being acquired digitally, stored within a server locally, and eventually accessed for diagnostic purposes, along with the rest of the patient data via the patient management software (PMS). A review of the literature shows the diagnostic performance of digital radiography is at least comparable to or even better than that of conventional radiography. Similarly, other digital diagnostic tools like caries detectors, cephalometric analysis software, and digital scanners were used for many years for the diagnosis and treatment planning purposes. The introduction of wireless charged-coupled device (CCD) sensors in early 2004 (Schick Technologies, Long Island City, NY) has moved digital radiography a step further into the wireless era. As with any emerging technology, there are concerns that should be looked into before adapting to the wireless environment. Foremost is the network security involved in the installation and usage of these wireless networks. This article deals with the existing standards and choices in wireless technologies that are available for implementation within a contemporary dental office. The network security protocols that protect the patient data and boost the efficiency of modern day dental clinics are enumerated.

Computer Security↗