PC-SyncBB: A privacy preserving collusion secure DCOP algorithm

In recent years, several studies proposed privacy-preserving algorithms for solving Distributed Constraint Optimization Problems (DCOPs). Those studies were based on existing DCOP solving algorithms, which they strengthened by implementing cryptographic weaponry that enabled performing the very same...

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Veröffentlicht in:Artificial intelligence 2021-08, Vol.297, p.103501, Article 103501
Hauptverfasser: Tassa, Tamir, Grinshpoun, Tal, Yanai, Avishay
Format: Artikel
Sprache:eng
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Zusammenfassung:In recent years, several studies proposed privacy-preserving algorithms for solving Distributed Constraint Optimization Problems (DCOPs). Those studies were based on existing DCOP solving algorithms, which they strengthened by implementing cryptographic weaponry that enabled performing the very same computation while protecting sensitive private data. 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. Our basic algorithm is secure against any coalition under the assumption of an honest majority (namely, the number of colluding agents is
ISSN:0004-3702
1872-7921
DOI:10.1016/j.artint.2021.103501