DeciTrustNET: A graph based trust and reputation framework for social networks

The world wide success of large scale social information systems with diverse purposes, such as e-commerce platforms, facilities sharing communities and social networks, make them a very promising paradigm for large scale information sharing and management. However the anonymity, distributed and open nature of these frameworks, that, on the one hand, foster the communication capabilities of their users, may contribute, on the other hand, to the propagation of low quality information, attacks and manipulations from users with malicious intentions. All of these risks could end up decreasing users’ confidence in these systems and in a reduction of their utilisation. With these issues in mind, the objective of this contribution is to create DeciTrustNET, a trust and reputation based framework for social networks that takes into consideration the users relationships, the historic evolution of their reputations and their profile similarity to develop a tamper resilient network that guarantees trustworthy communications and transactions. An extensive experimental analysis of the developed framework has been carried out confirming that the proposed approach supports robust trust and reputation establishment among the users, even in social network under the presence of malicious users. © 2020 Elsevier B.V.

Авторы
Ureña R.1 , Chiclana F.1, 2 , Herrera-Viedma E. 2, 3
Журнал
Издательство
Elsevier B.V.
Язык
Английский
Страницы
101-112
Статус
Опубликовано
Том
61
Год
2020
Организации
  • 1 Institute of Artificial Intelligence (IAI), School of Computer Science and Informatics, De Montfort University, Leicester, United Kingdom
  • 2 Andalusian Research Institute on Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, Spain
  • 3 Peoples’ Friendship University of Russia (RUDN University), Moscow, Russian Federation
Ключевые слова
Decision making; Influence; Opinion dynamics; Reputation; Social networks; Trust
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