# Adaptive Communication Networks with Privacy Guarantees

## TL;DR

This paper introduces an observability-based algorithm for designing adaptive communication networks that dynamically modify their topology to enhance privacy against intruders, using graph theory and control principles.

## Contribution

It presents a novel method for selecting optimal communication weights and topology adjustments to maximize privacy in networks from a control theoretic perspective.

## Key findings

- The proposed algorithm effectively enhances network privacy.
- Adaptive topology changes reduce information exposure during intrusions.
- The method integrates graph theory with control for privacy guarantees.

## Abstract

Utilizing the concept of observability, in conjunction with tools from graph theory and optimization, this paper develops an algorithm for network synthesis with privacy guarantees. In particular, we propose an algorithm for the selection of optimal weights for the communication graph in order to maximize the privacy of nodes in the network, from a control theoretic perspective. In this direction, we propose an observability-based design of the communication topology that improves the privacy of the network in presence of an intruder. The resulting adaptive network responds to the intrusion by changing the topology of the network-in an online manner- in order to reduce the information exposed to the intruder.