Collaborative Planning with Confidentiality

  • Authors:
  • Max Kanovich;Paul Rowe;Andre Scedrov

  • Affiliations:
  • Queen Mary, University of London, London, UK;The MITRE Corporation, Bedford, USA;University of Pennsylvania, Philadelphia, USA

  • Venue:
  • Journal of Automated Reasoning
  • Year:
  • 2011

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Abstract

Collaboration among organizations or individuals is common.While these participants are often unwilling to share all their information with each other, some information sharing is unavoidable when achieving a common goal. The need to share information and the desire to keep it confidential are two competing notions which affect the outcome of a collaboration. This paper proposes a formal model of collaboration which addresses confidentiality concerns. We draw on the notion of a plan which originates in the AI literature. We use data confidentiality policies to assess confidentiality in transition systems whose actions have an equal number of predicates in their pre- and post-conditions. Under two natural notions of policy compliance, we show that it is PSPACE-complete to schedule a plan leading from a given initial state to a desired goal state while simultaneously deciding compliance with respect to the agents' policies.