Abstract
With the increased need of data sharing among multiple organizations, such as government organizations, financial corporations, medical hospitals and academic institutions, it is critical to ensure that data is trustworthy so that effective decisions can be made based on these data. In this paper, we first discuss motivations and requirement for data trustworthiness. We then present an architectural framework for a comprehensive system for trustworthiness assurance. We then discuss an important issue in our framework, that is, the evaluation of data provenance and survey a trust model for estimating the confidence level of the data and the trust level of data providers. By taking into account confidence about data provenance, we introduce an approach for policy observing query evaluation. We highlight open research issues and research directions throughout the paper.
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Bertino, E., Dai, C., Kantarcioglu, M. (2009). The Challenge of Assuring Data Trustworthiness. In: Zhou, X., Yokota, H., Deng, K., Liu, Q. (eds) Database Systems for Advanced Applications. DASFAA 2009. Lecture Notes in Computer Science, vol 5463. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00887-0_2
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DOI: https://doi.org/10.1007/978-3-642-00887-0_2
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