A Controllable False Data Injection Attack for a Cyber Physical System

Janghoon Yang

doi:10.1109/access.2021.3049228

Abstract

With the evolution of the Internet of Things (IoT), various types of devices and massive systems comprising national infrastructures such as a smart grid are connected on a network, which poses various types of security issues in a cyber physical system. In this paper, we propose two false data injection attacks, which are on the forward path and the feedback path of a control system. Both are designed with a controllable parameter which determines the degree of degradation. A defensive method of inversing a linear forward attack through estimating with least square or minimum mean squared method was developed. A conventional Kalman filter was considered as a defensive method for a noise injection attack on the feedback path. The numerical evaluation verifies that the parameters of the proposed attacks control the degree of performance degradation of the control system, and the proposed defenses can effectively defend the proposed attacks.

Highlights

With the evolution of Internet and mobile technology, everything is connected on a network
In the forward path, we propose a linear forward attack (LFA) which linearly transforms a control input to degrade the performance of a control system with linear quadratic Gaussian (LQG) control marginally while a noise injection attack (NIA) which adds random noise to increase the variance of the measurement noise is proposed in the feedback path
Since LFA affects a control inputs and NIA affects an observation as their direct effects can be seen in (12) and (14), the linear forward attack is designed to degrade linear quadratic regulator (LQR) performance while the NIA is designed to degrade the performance of state estimation

Summary

INTRODUCTION

With the evolution of Internet and mobile technology, everything is connected on a network. J. Yang: Controllable False Data Injection Attack for a CPS performance and security were quantified through modeling a dynamical system with Markov decision process (MDP) which can be seen as partially observable MDP (POMDP) in the perspective of the attacker with limited access to the system [9]. Attack detector and the intermittent message authentication were proposed to improve robust control for CPS operating on the resource-constrained network in the presence of the FDIA at the measurement [18]. The pretender covert attack degrades the performance with modified control input while replacing the measurement output with the one predicted from the model without attack. The various potential attacks and associated defenses need to be studied further To this end, CPS attacks in both the forward path and the feedback path at a control system are considered in the perspective of FDIA while existing research focuses on either one not both.

SYSTEM MODEL AND PROBLEM FORMULATION

A DEFENSE FOR THE LINEAR FORWARD ATTACK

NOISE INJECTION ATTACK AND DEFENSE

NUMERICAL SIMULATIONS

CONCLUSION