A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Defining and Modeling Forced Trust and Its Dependencies in Smart Environments
Tekijät: Halla-Aho, Lauri; Isoaho, Jouni; Virtanen, Seppo
Kustantaja: IEEE
Julkaisuvuosi: 2024
Journal: IEEE Access
Tietokannassa oleva lehden nimi: IEEE Access
Vuosikerta: 12
Aloitussivu: 105865
Lopetussivu: 105877
eISSN: 2169-3536
DOI: https://doi.org/10.1109/ACCESS.2024.3436048
Verkko-osoite: https://ieeexplore.ieee.org/document/10616007
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/457456878
Tiivistelmä
In this paper, the concept of forced trust in smart environments is defined. Consequently, a trust model for mapping trust dependencies within these environments is proposed to aid in early detection and mitigation of issues caused by forced trust. The model represents the trust relationships between parties with regard to data transfers occurring in smart environments. Using three example projects utilised in smart environments, the applicability of the model is demonstrated for identifying common risks experienced by citizens in such environments, including undisclosed data utilisation, mass surveillance, and regionally weak privacy and data protection laws. The proposed model is a basis for forming an overview of the trust landscape in information system and service-related projects. Additionally, it aids with analysing how the actions of these contributing parties could pose risks, for example, to the privacy or security of the data, and consequently propagate to the denizens of these environments.
In this paper, the concept of forced trust in smart environments is defined. Consequently, a trust model for mapping trust dependencies within these environments is proposed to aid in early detection and mitigation of issues caused by forced trust. The model represents the trust relationships between parties with regard to data transfers occurring in smart environments. Using three example projects utilised in smart environments, the applicability of the model is demonstrated for identifying common risks experienced by citizens in such environments, including undisclosed data utilisation, mass surveillance, and regionally weak privacy and data protection laws. The proposed model is a basis for forming an overview of the trust landscape in information system and service-related projects. Additionally, it aids with analysing how the actions of these contributing parties could pose risks, for example, to the privacy or security of the data, and consequently propagate to the denizens of these environments.
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