An intelligent trust-based access control model for affective crowdsourcing
In this study, a fuzzy expert system Trust-Based Access Control (TBAC) model for improving the Quality of crowdsourcing using emotional affective computing is presented. This model takes into consideration a pre-processing module consisting of three inputs such as crowd-workers category, trust metric and emotional mood-positivity. The outcome of this module was presented into intelligent module and defuzzified into post-processing module that grants access to the successful crowdworker within the permissible range of priority value (Dvalue). However, TBAC-affective crowdsourcing algorithm was developed and implemented using matlab 7.6.0 .Trust values are evaluated With Mood(WM) and Without Mood Effect (WME) respectively using fuzzy inference system (FIS) . The result shows that an unknown worker with a good trust value whose mood is bad produces a poor quality result despite the knowledge gained.
Keywords: Affective Computing, Crowdsourcing System, Fuzzy Expert Systems, Quality Control, Trust- based Access Control.