Collaborative Planning with Confidentiality

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.

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Correspondence to Max Kanovich.

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Research partially supported by OSD/ONR CIP/SW URI “Software Quality and Infrastructure Protection for Diffuse Computing” through ONR Grant N00014-01-1-0795, OSD/ONR CIP/SW URI “Trustworthy Infrastructure, Mechanisms, and Experimentation for Diffuse Computing” through ONR Grant N00014-04-1-0725, by ONR Grant N00014-07-1-1039, by OSD/AFOSR MURI “Collaborative policies and assured information sharing”, and by EPSRC Grant EP/D053625/1 “Modularity and Resource Separation”. Additional support from NSF Grants CNS-0429689, CNS-0524059, and CNS-0830949. Rowe’s affiliation with The MITRE Corporation is provided for identification purposes only, and is not intended to convey or imply MITRE’s concurrence with, or support for, the positions, opinions or viewpoints expressed by the author. Most of the work was done while Rowe was PhD student at the University of Pennsylvania. Approved for Public Release: 10-1569.

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Kanovich, M., Rowe, P. & Scedrov, A. Collaborative Planning with Confidentiality. J Autom Reasoning 46, 389–421 (2011). https://doi.org/10.1007/s10817-010-9190-1

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Keywords

  • Collaborative planning
  • Confidentiality
  • AI literature
  • Policy compliance