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Quantifying Privacy Leakage in Multi-Agent Planning

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Published:05 February 2018Publication History
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Abstract

Multi-agent planning using MA-STRIPS–related models is often motivated by the preservation of private information. Such a motivation is not only natural for multi-agent systems but also is one of the main reasons multi-agent planning problems cannot be solved with a centralized approach. Although the motivation is common in the literature, the formal treatment of privacy is often missing. In this article, we expand on a privacy measure based on information leakage introduced in previous work, where the leaked information is measured in terms of transition systems represented by the public part of the problem with regard to the information obtained during the planning process. Moreover, we present a general approach to computing privacy leakage of search-based multi-agent planners by utilizing search-tree reconstruction and classification of leaked superfluous information about the applicability of actions. Finally, we present an analysis of the privacy leakage of two well-known algorithms—multi-agent forward search (MAFS) and Secure-MAFS—both in general and on a particular example. The results of the analysis show that Secure-MAFS leaks less information than MAFS.

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        • Published in

          cover image ACM Transactions on Internet Technology
          ACM Transactions on Internet Technology  Volume 18, Issue 3
          Special Issue on Artificial Intelligence for Secruity and Privacy and Regular Papers
          August 2018
          314 pages
          ISSN:1533-5399
          EISSN:1557-6051
          DOI:10.1145/3185332
          • Editor:
          • Munindar P. Singh
          Issue’s Table of Contents

          Copyright © 2018 ACM

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 5 February 2018
          • Revised: 1 July 2017
          • Accepted: 1 July 2017
          • Received: 1 October 2016
          Published in toit Volume 18, Issue 3

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