Automating Trust Evaluation for Ensuring Information Quality

Abstract

Modern warfare's situation awareness and operation planning requires analyzing a vast amount of information, ranging broadly from intelligence reports to data from autonomous sensors. Correctly assessing the credibility of such information in a timely manner is as crucial to decision making as being able to obtain the information in the first place. However, manual information quality assessment is time-consuming and laborious, especially considering the amount of information that modern automated knowledge solutions can deliver. In this paper, we present a novel trust framework called the Personalized Trust Framework (PTF), which can assist military analysts to automate their trust evaluation process, and, as a result, significantly lighten the burden of information quality assessment. In other words, it provides a mechanism for end users to capture their trust reasoning in order for it to be automated by computers. In particulars, a user can specify how he selects a trust model based on information about the subject whose trustworthiness he needs to evaluate and how that trust model is configured. This trust evaluation process is then automated by the PTF making use of the trust models that can be flexibly plugged into the PTF by the user. By so doing, the PTF enable users to reuse and to personalize existing trust models to suit their requirements without having to reprogram them. Finally, this paper demonstrates a simple application of the PTF in automated credibility evaluation to ensure information quality.

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ORCID for TD Huynh: orcid.org/0000-0003-4937-2473

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