International Journal of Man-Machine Studies
A new paradigm for trusted systems
NSPW '92-93 Proceedings on the 1992-1993 workshop on New security paradigms
Computer
Enhancing Grid Security with Trust Management
SCC '04 Proceedings of the 2004 IEEE International Conference on Services Computing
Customizable Framework for Managing Trusted Components Deployed on Middleware
ICECCS '05 Proceedings of the 10th IEEE International Conference on Engineering of Complex Computer Systems
Leveraging architectural models to inject trust into software systems
SESS '05 Proceedings of the 2005 workshop on Software engineering for secure systems—building trustworthy applications
A Multi-Property Trust Model for Reconfiguring Component Software
QSIC '05 Proceedings of the Fifth International Conference on Quality Software
Hardware security appliances for trust
iTrust'03 Proceedings of the 1st international conference on Trust management
Trust-based protection of software component users and designers
iTrust'03 Proceedings of the 1st international conference on Trust management
Autonomic trust management in a component based software system
ATC'06 Proceedings of the Third international conference on Autonomic and Trusted Computing
A survey of trust in internet applications
IEEE Communications Surveys & Tutorials
Information theoretic framework of trust modeling and evaluation for ad hoc networks
IEEE Journal on Selected Areas in Communications
On trust models and trust evaluation metrics for ad hoc networks
IEEE Journal on Selected Areas in Communications
| Hi-index | 0.00 |
Trust has been recognized as an important factor for a component software platform. Inside the platform, trust can be controlled according to its evaluation result. Special control modes can be applied into the software platform in order to ensure a trustworthy system. In this paper, we present a methodology for trust control mode prediction and selection in order to support autonomic platform trust management. The methodology is based on Fuzzy Cognitive Maps. The simulation results show this method is effective for predicting and selecting the feasible trust control modes.