Article
Health Care Sciences & Services
Robin van Kessel, Madeleine Haig, Elias Mossialos
Summary: The health care sector is highly vulnerable to cybersecurity breaches, with 76% of incidents caused by basic web application attacks, errors, and system intrusions, leading to compromised health data and disrupted services. The European Commission's proposal, the EHDS, aims to give EU citizens control over their personal health data in a private and secure environment. However, there is a need for stronger security measures in the EHDS to protect EU citizens' health data from cyber threats.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Article
Computer Science, Theory & Methods
Amirreza Zamani, Tobias J. Oechtering, Mikael Skoglund
Summary: This paper studies a stochastic disclosure control problem using information-theoretic methods, designing a privacy mechanism to maximize disclosed information about useful data under a strong chi(2)-privacy criterion. By utilizing methods from Euclidean information geometry, the challenging optimization problem is reduced to finding the principal right-singular vector of a matrix characterizing the optimal privacy mechanism. In extensions, scenarios involving noisy messages and maximizing mutual information between variables while satisfying privacy criteria are considered.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2021)
Article
Multidisciplinary Sciences
Kai Packhaeuser, Sebastian Guendel, Nicolas Muenster, Christopher Syben, Vincent Christlein, Andreas Maier
Summary: With the rise of deep learning techniques, publicly available medical datasets are crucial for developing diagnostic algorithms in the medical field. However, it has been shown that deep learning systems can recover patient identities from chest X-ray data, posing a risk of privacy breach.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Artificial Intelligence
Laraib Javed, Adeel Anjum, Bello Musa Yakubu, Majid Iqbal, Syed Atif Moqurrab, Gautam Srivastava
Summary: In our technologically advanced world, data security is crucial for every individual, especially in the exchange of medical information. Existing techniques for preserving data security have limitations, but this work proposes a secure architecture and semantic approach based on blockchain, local differential privacy, and federated learning. The proposed framework addresses the vulnerabilities of current solutions and provides a trustless environment for data sharing.
Article
Health Care Sciences & Services
Ravi Aggarwal, Soma Farag, Guy Martin, Hutan Ashrafian, Ara Darzi
Summary: The survey highlighted low levels of AI knowledge among participants, with most being comfortable sharing health data with the NHS or universities but less so with commercial organizations. The majority supported AI research on health care data and imaging in a university setting, provided that concerns about privacy and consent processes were addressed.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Article
Computer Science, Software Engineering
Ciera Jaspan, Collin Green
Summary: This installment discusses the COVID-19 pandemic and its impact on employee privacy, productivity, and the future of hybrid work.
Article
Computer Science, Hardware & Architecture
Xiaojie Zhu, Erman Ayday, Roman Vitenberg
Summary: Due to the privacy concerns of genomic and phenotype data, data owners often outsource their data to cloud service providers (CSPs) for storage and analysis. In this work, we propose a solution that enables privacy-preserving search and analysis over encrypted genomic and phenotype data owned by multiple hospitals. We introduce encryption mechanisms for phenotype data and multi-key fully homomorphic encryption for genomic data, allowing efficient identification of case/control groups and computation of GWAS statistics without privacy violations.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2023)
Article
Computer Science, Information Systems
Antonio Lopez Martinez, Manuel Gil Perez, Antonio Ruiz-Martinez
Summary: This paper focuses on analyzing and researching the clinical environment from a security and privacy perspective. It introduces the ecosystem and stakeholders of the clinical environment, and examines the protocols implemented between clinical components. It also presents a use case of the patient sample life cycle, categorizes crucial clinical information, and identifies the threat model and security and privacy needs for the use case. The paper provides protection mechanisms and enabling technologies for each sensitivity level, and concludes with the main challenges and future steps for the use case.
Article
Computer Science, Information Systems
Xinyu Yang, Teng Wang, Xuebin Ren, Wei Yu
Summary: This paper comprehensively reviews and investigates existing schemes for providing differential privacy from a broad perspective, discussing issues such as privacy guarantees, effectiveness, and efficiency in improving data utility. The existing schemes are categorized into different mechanisms, with a focus on analyzing and comparing their concepts and principles, aiming to enhance data utility.
IEEE TRANSACTIONS ON BIG DATA
(2021)
Article
Computer Science, Information Systems
Mahit Kumar Paul, Md Rabiul Islam, A. H. M. Sarowar Sattar
Summary: This study introduces a four-stage data perturbation approach called NRoReM to achieve a balance between privacy protection and data utility, demonstrating better protection of individual privacy and data utility in experiments.
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS
(2021)
Review
Chemistry, Analytical
G. M. S. Ross, Y. Zhao, A. J. Bosman, A. Geballa-Koukoula, H. Zhou, C. T. Elliott, M. W. F. Nielen, K. Rafferty, G. IJ. Salentijn
Summary: Smartphones have become ubiquitous in modern society, with over 6 billion active subscriptions in 2021. They have evolved from a mere means of communication to powerful miniaturized computers capable of collecting and processing both passive and active information for and from users. Furthermore, smartphones are increasingly being used as detectors or interfaces in emerging smartphone-based sensors, enabling the development of portable healthcare and point-of-need systems for various applications. This article reviews the existing literature on smartphone-based sensors and discusses the technological, legal, and ethical challenges associated with their development, providing insights for the future ethical data handling and device development in analytical chemistry applications.
TRAC-TRENDS IN ANALYTICAL CHEMISTRY
(2023)
Article
Biochemical Research Methods
Diyue Bu, Xiaofeng Wang, Haixu Tang
Summary: This article demonstrates the inference of haplotypes from genomic data summaries without the need for the target's genome. Novel haplotypes can be reconstructed from allele frequencies in genomic datasets, leading to a haplotype-based membership inference algorithm for identifying target subjects in a case group.
Article
Computer Science, Interdisciplinary Applications
Yingxiang Huang, Xiaoqian Jiang, Rodney A. Gabriel, Lucila Ohno-Machado
Summary: Protecting patient data privacy is important and integration of data from different healthcare systems is challenging. Distributed algorithms can improve model calibration while preserving data privacy, though computational efficiency may be compromised.
JOURNAL OF BIOMEDICAL INFORMATICS
(2021)
Article
Engineering, Multidisciplinary
Lihua Yin, Jiyuan Feng, Hao Xun, Zhe Sun, Xiaochun Cheng
Summary: The paper introduces a new hybrid privacy-preserving method for addressing data leakage threats in existing federated learning training processes. It utilizes advanced functional encryption algorithms and local Bayesian differential privacy to enhance data protection, while also implementing Sparse Differential Gradient to improve transmission and storage efficiency.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2021)
Review
Computer Science, Information Systems
Mariana Cunha, Ricardo Mendes, Joao P. Vilela
Summary: This paper conducts a comprehensive study on heterogeneous data types, PPMs, and privacy protection tools, proposing a privacy taxonomy that links different data types with suitable PPMs. A systematic analysis of privacy protection solutions is presented, identifying open challenges and future directions in the development of novel PPMs.
COMPUTER SCIENCE REVIEW
(2021)
