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Provenance-Based Trust Estimation for Service Composition

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AI 2013: Advances in Artificial Intelligence (AI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8272))

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Abstract

Provenance information can greatly enhance transparency and accountability of shared services. In this paper, we introduce a trust estimation approach which can derive trust information based on the analysis of provenance data. This approach can utilize the value of provenance data, and enhance trust estimation in open dynamic environments.

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References

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Author information

Authors and Affiliations

  1. School of Computing and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand

    Jing Jiang & Quan Bai

Authors
  1. Jing Jiang
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  2. Quan Bai
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Editor information

Editors and Affiliations

  1. Department of Information Science, University of Otago, 9054, Dunedin, New Zealand

    Stephen Cranefield

  2. Macquarie University, 2109, Sydney, NSW, Australia

    Abhaya Nayak

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© 2013 Springer International Publishing Switzerland

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Jiang, J., Bai, Q. (2013). Provenance-Based Trust Estimation for Service Composition. In: Cranefield, S., Nayak, A. (eds) AI 2013: Advances in Artificial Intelligence. AI 2013. Lecture Notes in Computer Science(), vol 8272. Springer, Cham. https://doi.org/10.1007/978-3-319-03680-9_7

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  • DOI: https://doi.org/10.1007/978-3-319-03680-9_7

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03679-3

  • Online ISBN: 978-3-319-03680-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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