Privacy of Existence of Secrets: Introducing Steganographic DCOPs and Revisiting DCOP Frameworks

TL;DR

This paper highlights a previously overlooked privacy concern in Distributed Constraint Optimization problems, specifically the privacy of the existence of secrets, and proposes a new framework to address this issue.

Contribution

It introduces the concept of steganographic DCOPs to formalize the privacy of secret existence and revisits the DCOP framework to clarify assumptions and improve comparability.

Findings

Identifies privacy of secret existence as a critical concern in DCOPs

Proposes steganographic DCOPs to model secret existence privacy

Provides a structured approach to compare DCOP techniques

Abstract

Here we identify a type of privacy concern in Distributed Constraint Optimization (DCOPs) not previously addressed in literature, despite its importance and impact on the application field: the privacy of existence of secrets. Science only starts where metrics and assumptions are clearly defined. The area of Distributed Constraint Optimization has emerged at the intersection of the multi-agent system community and constraint programming. For the multi-agent community, the constraint optimization problems are an elegant way to express many of the problems occurring in trading and distributed robotics. For the theoretical constraint programming community the DCOPs are a natural extension of their main object of study, the constraint satisfaction problem. As such, the understanding of the DCOP framework has been refined with the needs of the two communities, but sometimes without spelling the new assumptions formally and therefore making it difficult to compare techniques. Here we give a direction to the efforts for structuring concepts in this area.