Optimal deception attack on networked vehicular cyber physical systems
Paper in proceedings, 2019

Herein, design of false data injection attack on a distributed cyber-physical system is considered. A stochastic process with linear dynamics and Gaussian noise is measured by multiple agent nodes, each equipped with multiple sensors. The agent nodes form a multi-hop network among themselves. Each agent node computes an estimate of the process by using its sensor observations and messages obtained from neighbouring nodes, via Kalman-consensus filtering. An external attacker, capable of arbitrarily manipulating the sensor observations of some or all agent nodes, injects errors into those sensor observations. The goal of the attacker is to steer the estimates at the agent nodes as close as possible to a pre-specified value, while respecting a constraint on the attack detection probability. To this end, a constrained optimization problem is formulated to find the optimal parameter values of a certain class of linear attacks. The parameters of linear attack are learnt on-line via a combination of stochastic approximation and online stochastic gradient descent. Numerical results demonstrate the efficacy of the attack.

Kalman-consensus filter

CPS security

false data injection

Distributed estimation

stochastic approximation.

Author

Moulik Choraria

Indian Institute of Technology Delhi

Arpan Chattopadhyay

Indian Institute of Technology Delhi

Urbashi Mitra

University of Southern California

Erik Ström

Chalmers, Electrical Engineering, Communication and Antenna Systems

Conference Record - Asilomar Conference on Signals, Systems and Computers

10586393 (ISSN)

Vol. 2019-November 1131-1135 9048730

53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
Pacific Grove, USA,

Subject Categories

Probability Theory and Statistics

Control Engineering

Signal Processing

DOI

10.1109/IEEECONF44664.2019.9048730

More information

Latest update

5/20/2020