Abstract
In recent years, several studies proposed privacy-preserving algorithms for solving Distributed Constraint Optimization Problems (DCOPs). All of those studies assumed that agents do not collude. In this study we propose the first privacy-preserving DCOP algorithm that is immune to coalitions, under the assumption of honest majority. Our algorithm - PC-SyncBB - is based on the classical Branch and Bound DCOP algorithm. It offers constraint, topology and decision privacy. We evaluate its performance on different benchmarks, problem sizes, and constraint densities. We show that achieving security against coalitions is feasible. As all existing privacy-preserving DCOP algorithms base their security on assuming solitary conduct of the agents, we view this study as an essential first step towards lifting this potentially harmful assumption in all those algorithms.
Original language | English |
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Title of host publication | Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019 |
Editors | Sarit Kraus |
Publisher | International Joint Conferences on Artificial Intelligence |
Pages | 4774-4780 |
Number of pages | 7 |
ISBN (Electronic) | 9780999241141 |
DOIs | |
State | Published - 2019 |
Event | 28th International Joint Conference on Artificial Intelligence, IJCAI 2019 - Macao, China Duration: 10 Aug 2019 → 16 Aug 2019 |
Publication series
Name | IJCAI International Joint Conference on Artificial Intelligence |
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Volume | 2019-August |
ISSN (Print) | 1045-0823 |
Conference
Conference | 28th International Joint Conference on Artificial Intelligence, IJCAI 2019 |
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Country/Territory | China |
City | Macao |
Period | 10/08/19 → 16/08/19 |
Bibliographical note
Publisher Copyright:© 2019 International Joint Conferences on Artificial Intelligence. All rights reserved.