Shadow Health-Related Data: Definition, Categorization, and User Perspectives
Détails
Télécharger: ElZein2024EuroUSEC.pdf (4395.21 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY 4.0
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_703F3D2D6542
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Institution
Titre
Shadow Health-Related Data: Definition, Categorization, and User Perspectives
Titre de la conférence
Proceedings of the European Symposium on Usable Security (EuroUSEC)
Adresse
Karlstad, Sweden
Statut éditorial
Publié
Date de publication
09/2024
Peer-reviewed
Oui
Langue
anglais
Résumé
Health-related data (HRD) about individuals are increasingly generated and processed. The sources and volume of such data have grown larger over the past years, including wearable devices, health-related mobile apps, and electronic health records. HRD are sensitive, have important privacy implications, and therefore hold a special status under existing privacy laws and regulations. In this work, we focus on what we refer to as "shadow" HRD, which are HRD that are generated and/or processed by individuals using general-purpose digital tools outside of a professional health care information system. Some examples are health-related queries made by individuals on general-purpose search engines and LLM-based chatbots, or medical appointments and contact information of health professionals synced to the cloud. Such data, and the privacy risks stemming from them, are often overlooked when studying digital health. Based on two focus group sessions (23 participants in total), we identified and categorized a broad variety of user behaviors, including the aforementioned examples, that lead to the creation of shadow HRD. Then, informed by this categorization, we designed a questionnaire and deployed it through an online survey (300 respondents) to assess the prevalence of such behaviors among the general public, as well as user awareness of (and concerns about) the privacy risks stemming from their shadow HRD. Our findings show that most respondents adopt numerous and diverse behaviors that create shadow HRD, and very few resort to mechanisms to protect their privacy.
Mots-clé
health-related data, privacy, user study
Open Access
Oui
Création de la notice
06/08/2024 23:11
Dernière modification de la notice
05/09/2024 9:00