Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/136933
Title: A language for trust modelling
Authors: Muller, Tim
Zhang, Jie
Liu, Yang
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2016
Source: Muller, T., Zhang, J. & Liu, Y. (2016). A language for trust modelling. International Conference on Autonomous Agents and Multiagent Systems, pp 1-12.
Conference: International Conference on Autonomous Agents and Multiagent Systems
Abstract: The computational trust paradigm supposes that it is possible to quantify trust relations that occur within some software systems. The paradigm covers a variety of trust systems, such as trust management systems, reputation systems and trust-based security systems. Different trust systems have different assumptions, and various trust models have been developed on top of these assumptions Typically, trust models are incomparable, or even mutually unintelligible; as a result their evaluation may be circular or biased. We propose a unified language to express the trust models and trust systems. Within the language, all trust models are comparable, and the problem of circularity or bias is mitigated. Moreover, given a complete set of assumptions in the language, a unique trust model is defined.
URI: https://hdl.handle.net/10356/136933
URL: http://ceur-ws.org/Vol-1578/
ISSN: http://ceur-ws.org/Vol-1578/
Schools: School of Computer Science and Engineering 
Rights: © 2016 International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). All rights reserved. This paper was published in International Conference on Autonomous Agents and Multiagent Systems and is made available with permission of International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Conference Papers

Files in This Item:
File Description SizeFormat 
A language for modelling.pdf293.76 kBAdobe PDFThumbnail
View/Open

Page view(s)

304
Updated on Jul 22, 2024

Download(s) 50

95
Updated on Jul 22, 2024

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.