Trust Evaluation of Data Provenance

نویسندگان

  • Chenyun Dai
  • Dan Lin
  • Elisa Bertino
  • Murat Kantarcioglu
چکیده

With the increased need of data sharing among multiple organizations like government organizations, financial corporations, medical hospitals and academic institutions, it is critical to ensure data integrity so that effective decisions can be made based on these data. An important component of any solution for assessing data integrity is represented by techniques and tools to evaluate the trustworthiness of data provenance. However, few efforts have been devoted to investigate approaches for assessing how trusted the data are, based in turn on an assessment of the data sources and intermediaries. To bridge this gap, we propose a data provenance trust model. Our trust model takes into account various factors that may affect the trustworthiness and, based on these factors, assigns trust scores to both data and data providers. Such trust scores represent key information based on which data users may decide whether to use the data and for which purposes.

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تاریخ انتشار 2008