# A Privacy Preserving Collusion Secure DCOP Algorithm

arXiv: https://arxiv.org/abs/1905.09013 · HTML: https://mlsanity.com/paper/1905.09013/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 May 2019.

## Built on by (most cited first, 1 of 1)

- [Distributed Multi-Agent Coordination Using Multi-Modal Foundation Models](https://mlsanity.com/paper/2501.14189/) (2025)

## Abstract (arXiv)

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.