7th International Conference on Collaborative Computing: Networking, Applications and Worksharing

Research Article

Provenance for Collaboration: Detecting Suspicious Behaviors and Assessing Trust in Information

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  • @INPROCEEDINGS{10.4108/icst.collaboratecom.2011.247131,
        author={M. David Allen and Adriane Chapman and Len Seligman and Barbara Blaustein},
        title={Provenance for Collaboration: Detecting Suspicious Behaviors and Assessing Trust in Information},
        proceedings={7th International Conference on Collaborative Computing: Networking, Applications and Worksharing},
        publisher={IEEE},
        proceedings_a={COLLABORATECOM},
        year={2012},
        month={4},
        keywords={provenance trust insider threat lineage pedigree},
        doi={10.4108/icst.collaboratecom.2011.247131}
    }
    
  • M. David Allen
    Adriane Chapman
    Len Seligman
    Barbara Blaustein
    Year: 2012
    Provenance for Collaboration: Detecting Suspicious Behaviors and Assessing Trust in Information
    COLLABORATECOM
    ICST
    DOI: 10.4108/icst.collaboratecom.2011.247131
M. David Allen1, Adriane Chapman1, Len Seligman1,*, Barbara Blaustein1
  • 1: MITRE
*Contact email: seligman@mitre.org

Abstract

Data collaborations allow users to draw upon diverse resources to solve complex problems. While collaborations enable a greater ability to manipulate data and services, they also create new security vulnerabilities. Collaboration participants need methods to detect suspicious behaviors (potentially caused by malicious insiders) and assess trust in information when it passes through many hands. In this work, we describe these challenges and introduce provenance as a way to solve them. We describe a provenance system, PLUS, and show how it can be used to assist in assessing trust and detecting suspicious behaviors. A preliminary study shows this to be a promising direction for future research.