Network Inspection Using Heterogeneous Sensors for Detecting Strategic Attacks

TL;DR

This paper models a strategic network inspection game with heterogeneous sensors, analytically characterizes Nash equilibria, and proposes a heuristic for optimal sensor placement to detect attacks effectively.

Contribution

It introduces a game-theoretic framework for network inspection with heterogeneous sensors and develops a heuristic solution for large-scale networks.

Findings

Analytical characterization of Nash equilibria in the inspection game.

A heuristic based on minimum set covers for strategy computation.

Computational results demonstrating effectiveness on a cyber-physical network.

Abstract

We consider a two-player network inspection game, in which a defender allocates sensors with potentially heterogeneous detection capabilities in order to detect multiple attacks caused by a strategic attacker. The objective of the defender (resp. attacker) is to minimize (resp. maximize) the expected number of undetected attacks by selecting a potentially randomized inspection (resp. attack) strategy. We analytically characterize Nash equilibria of this large-scale zero-sum game when every vulnerable network component can be monitored from a unique sensor location. We then leverage our equilibrium analysis to design a heuristic solution approach based on minimum set covers for computing inspection strategies in general. Our computational results on a benchmark cyber-physical distribution network illustrate the performance and computational tractability of our solution approach.