Skip to Main Content (Press Enter)

Logo UNIRC
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture
  • Attività
  • Competenze

UNI-FIND
Logo UNIRC

|

UNI-FIND

unirc.it
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture
  • Attività
  • Competenze
  1. Pubblicazioni

Applying Trust Patterns to Model Complex Trustworthiness in the Internet of Things

Articolo
Data di Pubblicazione:
2024
Citazione:
Applying Trust Patterns to Model Complex Trustworthiness in the Internet of Things / Messina, F., Rosaci, D., Sarnè, G.M.L.. - In: ELECTRONICS. - ISSN 2079-9292. - 13:11(2024), pp. 1-11. [10.3390/electronics13112107]
Abstract:
Key aspects of communities of the Internet of Things (IoT) smart objects presenting social aspects are represented by trust and reputation relationships between the objects. Several trustworthiness models have been presented in the literature in the context of multi-smart object community that could be adopted in the IoT scenario; however, most of these approaches represent the different dimensions of trust using scalar measures, then integrating these measures in a global trustworthiness value. In this paper, we discuss the limitation of this approach in the IoT context, highlighting the necessity of modeling complex trust relationships that cannot be captured by a vector-based model, and we propose a new trust model in which the trust perceived by an object with respect to another object is modeled by a directed, weighted graph whose vertices are trust dimensions and whose arcs represent relationships between trust dimensions. By using this new model, we provide the IoT community with the possibility of representing also situations in which an object does not know a trust dimension, e.g., reliability, but it is able to derive it from another one, e.g., honesty. The introduced model can represent any trust structure of the type illustrated above, in which several trust dimensions are mutually dependent.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Messina, Fabrizio; Rosaci, Domenico; Sarnè, Giuseppe M. L.
Autori di Ateneo:
ROSACI Domenico
Link alla scheda completa:
https://iris.unirc.it/handle/20.500.12318/145786
Link al Full Text:
https://iris.unirc.it//retrieve/handle/20.500.12318/145786/380538/Messina_2024_Electronics_Applying_Editor.pdf
Pubblicato in:
ELECTRONICS
Journal
  • Dati Generali

Dati Generali

URL

https://www.mdpi.com/2079-9292/13/11/2107
  • Utilizzo dei cookie

Realizzato con VIVO | Designed by Cineca | 26.6.0.0