dc.contributor.author | Martínez González, María Mercedes | |
dc.contributor.author | Pérez de la Fuente, Alejandro | |
dc.contributor.author | Aparicio De La Fuente, Amador | |
dc.contributor.author | Criado-Lozano, Pablo A. | |
dc.date.accessioned | 2024-12-25T16:42:58Z | |
dc.date.available | 2024-12-25T16:42:58Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2024). José Bravo, Chris Nugent, and Ian Cleland (eds.). Lecture Notes in Networks and Systems, vol. 1212, p. 522-533 | es |
dc.identifier.issn | 2367-3370 | es |
dc.identifier.uri | https://uvadoc.uva.es/handle/10324/72998 | |
dc.description.abstract | Mobile applications (apps) facilitate the management of
devices and sensors from mobile devices in IoE environments. However,
their use carries risks for the privacy of their users: many of them manage
personal data. The App-PI (App Privacy Impact) ecosystem analyzes the
impact of apps on privacy, addressing the challenge of knowing, under-
standing and mitigating these risks.
In App-PI, a metadata warehouse, a set of analysis tools that calcu-
late indicators, a visualization platform, and verification processes, col-
laborate. Data flows between these components to provide persons using
the visualization platform with accurate, reliable, and understandable
information. The warehouse hosts metadata related to the privacy and
security of mobile apps. The data flow starts with the collection and
integration of data hosted in the warehouse. The analysis tools use these
data to calculate indicators that provide objective measures of the risk
associated with each app. These values are the input for a verification
process based on static analysis, which provides confidence. To make it
easier for end users to understand these indicators, they are displayed
on the visualization platform with easy-to-understand charts. The flows
and usefulness of this ecosystem are shown for health and wellness apps,
characteristic of IoE environments. | es |
dc.format.mimetype | application/pdf | es |
dc.language.iso | spa | es |
dc.publisher | Springer Nature Switzerland | es |
dc.rights.accessRights | info:eu-repo/semantics/embargoedAccess | es |
dc.subject | privacidad, ciberseguridad | es |
dc.subject.classification | Privacy, Metadata, Mobile apps, Health apps, IoE | es |
dc.title | Using the Metadata-Based App-PI Ecosystem to Assess the Privacy Impact of Health Apps | es |
dc.type | info:eu-repo/semantics/article | es |
dc.identifier.doi | 10.1007/978-3-031-77571-0 | es |
dc.relation.publisherversion | http://dx.doi.org/10.1007/978-3-031-77571-0 | es |
dc.identifier.publicationfirstpage | 522 | es |
dc.identifier.publicationissue | 1212 | es |
dc.identifier.publicationlastpage | 533 | es |
dc.identifier.publicationtitle | Lecture Notes in Networks and Systems | es |
dc.identifier.publicationvolume | 1212 | es |
dc.peerreviewed | SI | es |
dc.description.project | This work is included in the activities of the strategic Cyberse- curity project “App-PI (App Privacy Impact): An ecosystem for the evaluation of the impact of apps for mobile devices on the privacy and security of their users”, which is carried out under a collaboration agreement between the University of Valladolid and the Spanish National Institute of Cybersecurity (INCIBE) for the promotion of strategic Cybersecurity projects in Spain, within the framework of the funds of the Recovery, Transformation and Resilience Plan, financed by the European Union (Next Generation). | es |
dc.identifier.essn | 2367-3389 | es |
dc.type.hasVersion | info:eu-repo/semantics/acceptedVersion | es |