Privacy-Friendly and Trustworthy Technology for Society

被引:0
|
作者
Anton Fedosov [1 ]
Aurelia Tamò-Larrieux [2 ]
Christoph Lutz [3 ]
Eduard Fosch-Villaronga [4 ]
Anto Čartolovni [5 ]
机构
[1] University of Applied Sciences and Arts Northwestern Switzerland,
[2] University of Lausanne,undefined
[3] BI Norwegian Business School,undefined
[4] Leiden University,undefined
[5] Catholic University of Croatia,undefined
来源
Digital Society | 2025年 / 4卷 / 1期
关键词
Privacy; Trust; Active and assisted living; Artificial intelligence;
D O I
10.1007/s44206-025-00167-w
中图分类号
学科分类号
摘要
We have witnessed an increased use of technology in every facet of our lives. These technologies come with great promises, such as enabling more independent living for older adults or people with physical disabilities, yet also fears, for instance, over privacy concerns or trust in automated systems. In this Topical Collection, we focus on Active and Assisted Living (AAL) technologies, which require trustworthiness and adherence to privacy regulations for successful adoption. The Collection contains six selected papers that address themes like privacy-by-design, trust in AI, and balancing privacy with technological innovation under regulations like GDPR and the AI Act. The presented articles emphasize the user-centered, privacy-friendly approaches to AAL designs, robust regulatory frameworks, and interdisciplinary methodologies to ensure ethical, trustworthy technologies.
引用
收藏
相关论文
共 50 条
  • [11] Secure and privacy-friendly logging for eGovernment services
    Wouters, Karel
    Simoens, Koen
    Lathouwers, Danny
    Preneel, Bart
    ARES 2008: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON AVAILABILITY, SECURITY AND RELIABILITY, 2008, : 1091 - +
  • [12] Privacy-Friendly Aggregation for the Smart-Grid
    Kursawe, Klaus
    Danezis, George
    Kohlweiss, Markulf
    PRIVACY ENHANCING TECHNOLOGIES, 2011, 6794 : 175 - +
  • [13] Privacy by Evidence: A Methodology to develop privacy-friendly software applications
    Barbosa, Pedro
    Brito, Andrey
    Almeida, Hyggo
    INFORMATION SCIENCES, 2020, 527 : 294 - 310
  • [14] Speranza: Usable, privacy-friendly software signing
    Merrill, Kelsey
    Newman, Zachary
    Torres-Arias, Santiago
    Sollins, Karen R.
    PROCEEDINGS OF THE 2023 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY, CCS 2023, 2023, : 3388 - 3402
  • [15] A privacy-friendly architecture for future cloud computing
    Petrlic, Ronald
    Sekula, Stephan
    Sorge, Christoph
    INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING, 2013, 4 (04) : 265 - 277
  • [16] ETHICAL ASSESSMENTS FOR A PRIVACY-FRIENDLY ARTIFICIAL INTELLIGENCE
    Morte Ferrer, Ricardo
    ARBOR-CIENCIA PENSAMIENTO Y CULTURA, 2021, 197 (802)
  • [17] A privacy-friendly loyalty system for electronic marketplaces
    Enzmann, M
    Schneider, M
    2004 IEEE INTERNATIONAL CONFERNECE ON E-TECHNOLOGY, E-COMMERE AND E-SERVICE, PROCEEDINGS, 2004, : 385 - 393
  • [18] Privacy-friendly statistical counting for pedestrian dynamics
    Stanciu, Valeriu-Daniel
    van Steen, Maarten
    Dobre, Ciprian
    Peter, Andreas
    COMPUTER COMMUNICATIONS, 2023, 211 : 178 - 192
  • [19] Privacy-Friendly Skies: Models, Metrics, & Solutions
    SamPigethaya, Krishna
    Poovendran, Radha
    Taylor, Steve
    2013 IEEE/AIAA 32ND DIGITAL AVIONICS SYSTEMS CONFERENCE (DASC), 2013,
  • [20] Cell-based privacy-friendly roadpricing
    Garcia, Flavio D.
    Verheul, Eric R.
    Jacobs, Bart
    COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2013, 65 (05) : 774 - 785