相关论文: Formal Analysis of an E-Health Protocol
Online medical consultation platforms, while convenient, are undermined by significant privacy risks that erode user trust. We first conducted in-depth semi-structured interviews with 12 users to understand their perceptions of security and…
eHealth has expanded hugely over the last fifteen years and continues to evolve, providing greater benefits for patients, health care professionals and providers alike. The technologies that support these systems have become increasingly…
Telecare medical information systems are gaining rapid popularity in terms of providing the delivery of online health-related services such as online remote health profile access for patients and doctors. Due to being installed entirely on…
Electronic medical records (EMR) contain sensitive personal information. For example, they may include details about infectious diseases, such as human immunodeficiency virus (HIV), or they may contain information about a mental illness.…
Digital medical imaging laboratories contain many distinct types of equipment provided by different manufacturers. Interoperability is a critical issue and the DICOM protocol is a de facto standard in those environments. However,…
In the era of digital health and artificial intelligence, the management of patient data privacy has become increasingly complex, with significant implications for global health equity and patient trust. This paper introduces a novel…
Privacy is a major good for users of personalized services such as recommender systems. When applied to the field of health informatics, privacy concerns of users may be amplified, but the possible utility of such services is also high.…
Healthcare data contains some of the most sensitive information about an individual, yet sharing this data with healthcare practitioners can significantly enhance patient care and support research efforts. However, current systems for…
Differential privacy is a popular privacy model within the research community because of the strong privacy guarantee it offers, namely that the presence or absence of any individual in a data set does not significantly influence the…
The wide adoption of wearable smart devices with onboard cameras greatly increases people's concern on privacy infringement. Here we explore the possibility of easing persons from photos captured by smart devices according to their privacy…
E-values have gained prominence as flexible tools for statistical inference and risk control, enabling anytime- and post-hoc-valid procedures under minimal assumptions. However, many real-world applications fundamentally rely on sensitive…
Electronic Health Records (EHRs) store sensitive patient information, necessitating stringent access control and sharing mechanisms to uphold data security and comply with privacy regulations such as the General Data Protection Regulation…
Background: The integration of the General Data Protection Regulation (GDPR) and the Medical Device Regulation (MDR) creates complexities in conducting Data Protection Impact Assessments (DPIAs) for medical devices. The adoption of…
There is an abundance of digital sexual and reproductive health technologies that presents a concern regarding their potential sensitive data breaches. We analyzed 15 Internet of Things (IoT) devices with sexual and reproductive tracking…
Unstructured textual data is at the heart of healthcare systems. For obvious privacy reasons, these documents are not accessible to researchers as long as they contain personally identifiable information. One way to share this data while…
In this paper, we study the privacy of online health data. We present a novel online health data De-Anonymization (DA) framework, named De-Health. De-Health consists of two phases: Top-K DA, which identifies a candidate set for each…
The global health threat from COVID-19 has been controlled in a number of instances by large-scale testing and contact tracing efforts. We created this document to suggest three functionalities on how we might best harness computing…
Context: System Theoretic Process Analysis for Privacy (STPA-Priv) is a novel privacy risk elicitation method using a top down approach. It has not gotten very much attention but may offer a convenient structured approach and generation of…
E-health services handle a massive amount of sensitive data, requiring reliability and privacy. The advent of new technologies drives e-health services into their continuous provision outside traditional care institutions. This creates…
As digital threats continue to grow, organizations must find ways to enhance security while protecting user privacy. This paper explores how artificial intelligence (AI) plays a crucial role in achieving this balance. AI technologies can…