Title
Detection in Adversarial Environments
Abstract
We propose new game theoretic approaches to estimate a binary random variable based on sensor measurements that may have been corrupted by a cyber-attacker. The estimation problem is formulated as a zero-sum partial information game in which a detector attempts to minimize the probability of an estimation error and an attacker attempts to maximize this probability. While this problem can be solved exactly by reducing it to the computation of the value of a matrix, this approach is computationally feasible only for a small number of sensors. The two key results of this paper provide complementary computationally efficient solutions to the construction of the optimal detector. The first result provides an explicit formula for the optimal detector but it is only valid when the number of sensors is roughly smaller than two over the probability of sensor errors. In contrast, the detector provided by the second result is valid for an arbitrary number of sensor. While it may result in a probability of estimation error that is ϵ above the minimum achievable, we show that this error ϵ is small when the number of sensors is large, which is precisely the case for which the first result does not apply.
Year
DOI
Venue
2014
10.1109/TAC.2014.2351671
Automatic Control, IEEE Transactions  
Keywords
DocType
Volume
estimation theory,game theory,probability,adversarial environments,binary random variable,cyber-attacker,estimation error,game theoretic approach,probability,sensor measurements,Adversarial detection,Byzantine sensors,cyber security,estimation,zero-sum games
Journal
59
Issue
ISSN
Citations 
12
0018-9286
4
PageRank 
References 
Authors
0.49
0
4
Name
Order
Citations
PageRank
Kyriakos G. Vamvoudakis1274.74
Joao P. Hespanha259158.43
Bruno Sinopoli32837188.08
Yilin Mo489151.51