Affiliations: Laboratory for Intelligent Processes and Systems, The University of Texas at Austin, Austin, TX, USA
Correspondence:
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Corresponding author: David DeAngelis, Laboratory for Intelligent Processes and Systems, The University of Texas at Austin, 1 University Station C5000, Austin, TX 78712-0240, USA. Tel.: +1 512 471 5350; Fax: +1 512 471 5445; E-mail: dave@lips.utexas.edu.
Abstract: The concept of trust as presented here focuses on the trustworthiness, or reliability, of information and information sources. Decision makers, or agents, can create judgments based on previous experience with other agents and by reputation information received from allied agents. These judgments, or trust assessments, are used to predict the behavior of other agents and analyze the trustworthiness, truthfulness, or quality of information. Research concepts have been developed within the trust community, and they are most commonly applied to multi-agent systems research. This work attempts to show that trust research can be directly applied to security problems. Modern trust concepts enforce soft security which can be applied in addition to conventional security methods to build a more robust secure system. This article examines two trust based techniques and demonstrates their basic effectiveness using empirical experimentation. These techniques are then applied in a case study drawn from a more robust domain concerning confidential message transmission. The benefits of applying trust-based techniques to secure a system are measurable, and the costs associated with such techniques are scalable to even the most resource constrained systems.
Keywords: Information privacy and security, trust and reputation, empirical evaluation, distributed artificial intelligence
