POSTER: Data quality evaluation: integrating security and accuracy

  • Authors:

  • Leon Reznik;Elisa Bertino

  • Affiliations:

  • Rochester Institute of Technology, Rochester, NY, USA;Purdue University, West Lafayette, IN, USA

  • Venue:
  • Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
  • Year:
  • 2013

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Abstract

Data quality (DQ) is essential to achieve data trustworthiness, as it assures that data is free of errors, complete, and consistent. This paper proposes an approach to evaluate DQ in multichannel sensor networks and systems with heterogeneous data sources. The approach integrates various DQ indicators ranging from traditional data accuracy metrics to network security and business performance measures. It demonstrates the advantage of including security metrics into the DQ evaluation for the design optimization of data fusion procedures and even the whole data collection and communication systems. The DQ metrics composition and calculus are discussed. However, the major attention is paid to the analysis of the relationship between conventional data accuracy metrics and network security indicators.