Evader Interdiction and Collateral Damage

TL;DR

This paper studies optimal sensor placement strategies in network interdiction problems to intercept evaders with various movement models, providing algorithms for special cases and complexity results for general graphs.

Contribution

It introduces optimal algorithms for specific graph classes and establishes hardness and approximation bounds for general network interdiction problems involving reactive and oblivious evaders.

Findings

Optimal sensor placement algorithms for certain graph classes.

Hardness results for general graph interdiction problems.

Approximation algorithms with performance bounds.

Abstract

In network interdiction problems, evaders (e.g., hostile agents or data packets) may be moving through a network towards targets and we wish to choose locations for sensors in order to intercept the evaders before they reach their destinations. The evaders might follow deterministic routes or Markov chains, or they may be reactive}, i.e., able to change their routes in order to avoid sensors placed to detect them. The challenge in such problems is to choose sensor locations economically, balancing security gains with costs, including the inconvenience sensors inflict upon innocent travelers. We study the objectives of 1) maximizing the number of evaders captured when limited by a budget on sensing cost and 2) capturing all evaders as cheaply as possible. We give optimal sensor placement algorithms for several classes of special graphs and hardness and approximation results for general graphs, including for deterministic or Markov chain-based and reactive or oblivious evaders. In a similar-sounding but fundamentally different problem setting posed by Rubinstein and Glazer where both evaders and innocent travelers are reactive, we again give optimal algorithms for special cases and hardness and approximation results on general graphs.