Optimal deception attack on networked vehicular cyber physical systems
Paper i proceeding, 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.

stochastic approximation.

Kalman-consensus filter

Distributed estimation

false data injection

CPS security

Författare

Moulik Choraria

Indian Institute of Technology

Arpan Chattopadhyay

Indian Institute of Technology

Urbashi Mitra

University of Southern California

Erik Ström

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Conference Record - Asilomar Conference on Signals, Systems and Computers

10586393 (ISSN)

Vol. 2019-November 1131-1135 9048730
978-172814300-2 (ISBN)

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

Ämneskategorier

Sannolikhetsteori och statistik

Reglerteknik

Signalbehandling

DOI

10.1109/IEEECONF44664.2019.9048730

Mer information

Senast uppdaterat

2024-05-29