# Allocating Limited Resources to Protect a Massive Number of Targets using a Game Theoretic Model

## TL;DR

This paper introduces a game theoretic model for resource allocation in security, incorporating action costs and bounded rational attacker behavior, demonstrating improved utility and efficiency over other strategies.

## Contribution

It presents a novel game theoretic framework that includes action costs and models bounded rational attacker behavior for better resource allocation in security.

## Key findings

- The proposed strategy outperforms others in utility.
- Incorporating action costs improves model realism.
- Model effectively simulates human attacker behavior.

## Abstract

Resource allocation is the process of optimizing the rare resources. In the area of security, how to allocate limited resources to protect a massive number of targets is especially challenging. This paper addresses this resource allocation issue by constructing a game theoretic model. A defender and an attacker are players and the interaction is formulated as a trade-off between protecting targets and consuming resources. The action cost which is a necessary role of consuming resource, is considered in the proposed model. Additionally, a bounded rational behavior model (Quantal Response, QR), which simulates a human attacker of the adversarial nature, is introduced to improve the proposed model. To validate the proposed model, we compare the different utility functions and resource allocation strategies. The comparison results suggest that the proposed resource allocation strategy performs better than others in the perspective of utility and resource effectiveness.