Privacy-aware Adaptive Scheduling for Coalition Operations

Karen L. Myers, Tom Lee, Laura Tam, Jose Manuel Calderon Trilla, Ben Davis, Stephen Magill

Keywords: Scheduling, Quantitative Information Flow, Adaptive Workflow Management, Policy

TL;DR: Privacy can be thought about in the same way as other resources in planning

Abstract: Coalition operations are essential for responding to the increasing number of world-wide incidents that require large-scale humanitarian assistance. Many nations and non-governmental organizations regularly coordinate to address such problems but their cooperation is often impeded by limits on what information they are able to share. In this paper, we consider the use of an advanced cryptographic technique called secure multi-party computation to enable coalition members to achieve joint objectives while still meeting privacy requirements. Our particular focus is on a multi-nation aid delivery scheduling task that involves coordinating when and where various aid provider nations will deliver relief materials after the occurrence of a natural disaster. Even with the use of secure multi-party computation technology, information about private data can leak. We describe how the emerging field of quantitative information flow can be used to help data owners understand the extent to which private data might become vulnerable as the result of possible or actual scheduling operations, and to enable automated adjustments of the scheduling process to ensure privacy requirements

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