A fuzzy and probabilistic logic based representational model of certain trust model

Kawser Wazed Nafi, Tonny Shekha Kar, Amjad Hossain, M. M.A. Hashem

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

At the present world of IT, ensuring Trust is a very important topic; especially for service oriented systems. In the present trust models, particularly in Certain Trust model the main parameters of the representational model portion are uncertainty and average rating which are based on propositional logic where the possible values for them are considered between 0 and 1. In this paper we have proposed a new representational model for Certain Trust model based on probabilistic logic and fuzzy logic related with propositional logic to ensure trustworthiness of systems like cloud computing, internet, website, e-commerce, etc. We have proposed two new parameters - trust T and behavioral probability P, which will help the users and the developers of the service oriented systems to understand its' present condition easily. Fuzzy Associative Memory(FAM) are used for representing rule matrices for different inference rules and linguistic variables are also designed for this new representational model.

Original languageEnglish (US)
Title of host publication2012 International Conference on Informatics, Electronics and Vision, ICIEV 2012
Pages1000-1005
Number of pages6
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 1st International Conference on Informatics, Electronics and Vision, ICIEV 2012 - Dhaka, Bangladesh
Duration: May 18 2012May 19 2012

Publication series

Name2012 International Conference on Informatics, Electronics and Vision, ICIEV 2012

Conference

Conference2012 1st International Conference on Informatics, Electronics and Vision, ICIEV 2012
Country/TerritoryBangladesh
CityDhaka
Period5/18/125/19/12

Keywords

  • Certain Logic
  • Certain Trust
  • Cloud Computing
  • FAM Rule
  • Fuzzy Logic
  • Probabilitics Logic

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Information Systems
  • Electrical and Electronic Engineering

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