Attacking the V:On the resiliency of adaptive-horizon MPC


Inspired by the emerging problem of CPS security, we introduce the concept of controller-attacker games. A controller-attacker game is a two-player stochastic game, where the two players, a controller and an attacker, have antagonistic objectives. A controller-attacker game is formulated in terms of a Markov Decision Process (MDP), with the controller and the attacker jointly determining the MDP’s transition probabilities. We also introduce the class of controller-attacker games we call V-formation games, where the goal of the controller is to maneuver the plant (a simple model of flocking dynamics) into a V-formation, and the goal of the attacker is to prevent the controller from doing so. Controllers in V-formation games utilize a new formulation of model-predictive control we have developed called Adaptive-Horizon MPC (AMPC), giving them extraordinary power: we prove that under certain controllability conditions, an AMPC controller can attain V-formation with probability 1. We evaluate AMPC’s performance on V-formation games using statistical model checking. Our experiments demonstrate that (a) as we increase the power of the attacker, the AMPC controller adapts by suitably increasing its horizon, and thus demonstrates resiliency to a variety of attacks; and (b) an intelligent attacker can significantly outperform its naive counterpart.

Publication DOI:
Divisions: College of Engineering & Physical Sciences
Funding Information: Acknowledgments. Research supported in part by the Doctoral Program Logical Methods in Computer Science and the Austrian National Research Network RiSE/SHiNE (S11412-N23) project funded by the Austrian Science Fund (FWF) project W1255-N23, AFOSR Grant FA9
Additional Information: © Springer International Publishing AG 2017. The final publication is available at Springer via
Event Title: 15th International Conference on Automated Technology for Verification and Analysis, ATVA 2017
Event Type: Other
Event Dates: 2017-10-03 - 2017-10-06
Uncontrolled Keywords: Theoretical Computer Science,Computer Science(all)
ISBN: 9783319681665
Last Modified: 17 Apr 2024 07:28
Date Deposited: 07 Dec 2018 11:59
Full Text Link: https://arxiv.o ... /abs/1702.00290
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://link.sp ... -319-68167-2_29 (Publisher URL)
PURE Output Type: Conference contribution
Published Date: 2017-09-27
Published Online Date: 2017-09-27
Accepted Date: 2017-01-01
Authors: Tiwari, Ashish
Smolka, Scott A.
Esterle, Lukas (ORCID Profile 0000-0002-0248-1552)
Lukina, Anna
Yang, Junxing
Grosu, Radu



Version: Accepted Version

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