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

Xu Liu,Xiaoqiang Di,Ligang Cong,Huamin Yang,Huan Wang,Yuming Jiang,Jianping Zhao,Jinqing Li

doi:10.1155/2019/5475341

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.

Highlights

Resource allocation has always been a complex problem, especially when driven by security requirements
In the AWS re:Invent 2014, the AWS engineer claimed that Amazon had nearly 28 total sets across the world, each of which has one or more data centers with a typical facility containing 50,000 to 80,000 servers [2]. To protect these servers against attack and maintain their consistent operation, cloud providers will implement security strategy. They can protect targets by setting up resource reservations to analyze the operation of targets and respond the attack quickly, which is followed by a lot of resource consumption [3]
The attacker has the ability to consider the situation from the perspective of the defender, the attacker might take abrupt actions that lie outside the defender’s expectations. This type of attacker, who is of the adversarial nature, can be simulated by the quantal response (QR) model, which has received widespread support in the literature on modeling human behavior in games [17]. We introduce it into the proposed Game Theoretic Resource Allocation (GTRA) model to simulate adversarial reasoning

Summary

Introduction

Resource allocation has always been a complex problem, especially when driven by security requirements. In the AWS re:Invent 2014, the AWS engineer claimed that Amazon had nearly 28 total sets across the world, each of which has one or more data centers with a typical facility containing 50,000 to 80,000 servers [2] To protect these servers against attack and maintain their consistent operation, cloud providers will implement security strategy. We include cost in the Stackelberg game [16] utility function and analyze the impact of different parameter value configurations on the defender’s utility Since both the defender and the attacker are intelligent and have the perspective-taking ability, we consider an interaction in which the defender designs a resource allocation strategy first and the attacker subsequently develops an attack strategy. The final section summarizes the paper and outlines directions for future work

Related Work

Problem Description

Model Formulation

Numerical Study

Findings

Conclusion