On some Challenges for Online Trust and Reputation Systems
MetadataVis full innførsel
The Internet form a globally distributed network that provides a ubiquitous medium for interaction, the exchange of ideas, and commerce. The web is pervading our everyday lives in ways that were unimaginable even ten years ago. The evolving use of the web requires robust and efficient trust and reputation management mechanisms. During the past decade, online trust and reputation systems have provided cogent answers to emerging challenges in the global computing infrastructures relating to computer and network security, electronic commerce, virtual enterprises, social networks and cloud computing. The goal of these systems in such global computing infrastructures is to allow entities to reason about the trustworthiness of other entities and to make autonomous decisions on the basis of trust. This requires the development of computational trust models that enable entities to reason about trust and to verify the properties of a particular interaction. The robustness of these mechanisms, which is one of the critical factors for the success of this technology, is currently not being sufficiently addressed. The global computing infrastructure is highly dynamic with continuously appearing and disappearing entities and services. It is vital that the associated computational trust model is able to incorporate this dynamism and that equally flexible legislative and regulatory frameworks emerge. In this thesis, we present an overview of the characteristics of the existing characteristics of the existing online trust and reputation models and systems through a multidimensional framework, which can serve as a basis to understand the current state of the art in the area. The critical open challenges that limit the effectiveness of today’s trust and reputation systems are discussed by providing a comprehensive literature review. Furthermore, we present a set of our contributions as a way to address some of these challenges and propose prospectives for online trust and reputation systems.
Består avTavakolifard, Mozhgan; Almeroth, Kevin C.. Social Computing. IEEE Network. (ISSN 0890-8044). 26(4): 53-58, 2012. 1109/MNET.2012.6246753.
tavakolifard, Mozhgan; Almeroth, Kevin; Ozturk, Pinar. Subjectivity handling of ratings for Trust and Reputation systems: An Abductive Reasoning Approach. International Journal of Digital Content Technology and its Applications. (ISSN 1975-9339), 2011.
Tavakolifard, Mozhgan; Almeroth, Kevin C.. The Hidden Trust Network underly ing Twitter. .
Tavakolifard, Mozhgan; Øzturk, Pinar. Situation-based Trust Adjustment by Conditional Reasoning. Proceedings of the Networking and Electronic Commerce Research Conference, 2011.
Tavakolifard, Mozhgan; Knapskog, Svein Johan. Trust Evaluation Initialization Using Contextual Information. Proceedings of the The International Conference on Management of Emergent Digital EcoSystems, 2011. 10.1145/2077489.2077491.
Tavakolifard, Mozhgan; Knapskog, Svein Johan. A Probabilistic Reputation Algorithm for Decentralized Multi-Agent Environments. Electronical Notes in Theoretical Computer Science. (ISSN 1571-0661). 244: 139-149, 2009. 10.1016/j.entcs.2009.07.043.
Tavakolifard, Mozhgan; Herrmann, Peter; Knapskog, Svein J.. Inferring Trust Based on Similarity with TILLIT. TRUST MANAGEMENT III: 133-148, 2009.
Tavakolifard, Mozhgan; Herrmann, Peter; Ozturk, Pinar. Analogical Trust Reasoning. TRUST MANAGEMENT III: 149-163, 2009.