On Location Hiding in Distributed Systems

TL;DR

This paper investigates algorithms for mobile agents to hide their initial positions in a graph from an adversary, analyzing the complexity and optimal strategies under various knowledge and memory constraints.

Contribution

It introduces a formal definition of well-hiding algorithms and analyzes their efficiency in different scenarios, including known and unknown topologies, with and without memory.

Findings

Optimal hiding algorithms depend on graph diameter and size.

Deterministic hiding is impossible without memory in unknown topologies.

Randomized algorithms enable effective hiding in single-agent unknown topology scenarios.

Abstract

We consider the following problem - a group of mobile agents perform some task on a terrain modeled as a graph. In a given moment of time an adversary gets an access to the graph and positions of the agents. Shortly before adversary's observation the mobile agents have a chance to relocate themselves in order to hide their initial configuration. We assume that the initial configuration may possibly reveal to the adversary some information about the task they performed. Clearly agents have to change their location in possibly short time using minimal energy. In our paper we introduce a definition of a \emph{well hiding} algorithm in which the starting and final configurations of the agents have small mutual information. Then we discuss the influence of various features of the model on the running time of the optimal well-hiding algorithm. We show that if the topology of the graph is known to the agents, then the number of steps proportional to the diameter of the graph is sufficient and necessary. In the unknown topology scenario we only consider a single agent case. We first show that the task is impossible in the deterministic case if the agent has no memory. Then we present a polynomial randomized algorithm. Finally in the model with memory we show that the number of steps proportional to the number of edges of the graph is sufficient and necessary. In some sense we investigate how complex is the problem of "losing" information about location (both physical and logical) for different settings.