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Your search keyword '"Li, Yuzhe"' showing total 6 results
Start Over Author "Li, Yuzhe" Topic game theory
6 results on '"Li, Yuzhe"'

1. False Data Injection Attacks on Networked Control Systems: A Stackelberg Game Analysis.

Author

Li, Yuzhe, Shi, Dawei, and Chen, Tongwen

Subjects
*H2 control, *CYBERTERRORISM, *DATA security, *DENIAL of service attacks, *GAME theory
Abstract

In this paper, a security problem in networked control systems (NCS) is studied. In a standard linear quadratic Gaussian (LQG) control scenario in NCS, a so-called false data injection attack could be launched by a malicious attacker to deteriorate the system performance without being detected. To defend against such attacks, a defender on the NCS side needs to allocate defense resources among the sensors to secure the data, and the defense investment determines the costs of compromising certain sensors. After observing the defender’ action, the attacker decides the target sensors to compromise. While both sides are subject to the resource constraints, the interactive decision-making between the defender and the attacker is investigated in a Stackelberg game (leader–follower game) framework. The optimal solutions for both sides under different types of budget constraints are analyzed. Simulation examples are provided to illustrate the main results. [ABSTRACT FROM AUTHOR]

Published
2018
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2. Stochastic detection against deception attacks in CPS: Performance evaluation and game-theoretic analysis.

Author

Li, Yuzhe, Yang, Yake, Chai, Tianyou, and Chen, Tongwen

Subjects
*MULTISENSOR data fusion, *DECEPTION, *CYBER physical systems, *PERFORMANCE standards, *DETECTORS, *ELECTRONIC data processing
Abstract

In this paper, we consider a security problem of remote state estimation in cyber–physical systems (CPS). The state measurements of a dynamic process, obtained by wireless sensors, may be modified deceptively by a malicious attacker, which may bypass a standard χ 2 detector. On the other hand, the estimation performance with a standard χ 2 detector typically is also difficult to analyze. As such, a stochastic detection mechanism with a varying triggering threshold is proposed. We provide an analytical performance evaluation for the estimation with the proposed detector, and propose a potential countermeasure to actively defend the deception attacks with the proposed detector. The interactive decision-making process between the system with the countermeasure and the attacker is then studied under a game-theoretic framework. In addition, we also extend the stochastic false data detection problem into a multi-sensor setting with a sequential data fusion process and more general attacking patterns, and analyze the estimation performance. Simulations are provided to illustrate the developed results. [ABSTRACT FROM AUTHOR]

Published
2022
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3. Jamming attack on Cyber-Physical Systems: A game-theoretic approach.

Author

Li, Yuzhe, Shi, Ling, Cheng, Peng, Chen, Jiming, and Quevedo, Daniel E.

Abstract

We consider security issues in Cyber-Physical Systems (CPSs). A sensor node communicates with a remote estimator through a wireless channel which may be jammed by an external attacker. With energy constraints for both the sensor and the attacker, the interactive decision making process of when to send and when to attack is studied. We formulate a game-theoretical framework and prove that the optimal strategies for both sides constitute a Nash equilibrium. The derivation of the optimal strategies for both sides is also provided with examples. [ABSTRACT FROM PUBLISHER]

Published
2013
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4. Jamming Attacks on Remote State Estimation in Cyber-Physical Systems: A Game-Theoretic Approach.

Author

Li, Yuzhe, Shi, Ling, Cheng, Peng, Chen, Jiming, and Quevedo, Daniel E.

Subjects
*CYBER physical systems, *DENIAL of service attacks, *GAME theory, *MARKOV processes, *COST functions
Abstract

We consider security issues in remote state estimation of Cyber-Physical Systems (CPS). A sensor node communicates with a remote estimator through a wireless channel which may be jammed by an external attacker. With energy constraints for both the sensor and the attacker, the interactive decision making process of when to send and when to attack is studied. We formulate a game-theoretic framework and prove that the optimal strategies for both sides constitute a Nash equilibrium of a zero-sum game. To tackle the computation complexity issues, we present a constraint-relaxed problem and provide corresponding solutions using Markov chain theory. [ABSTRACT FROM PUBLISHER]

Published
2015
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5. A game-theoretic approach to fake-acknowledgment attack on cyber-physical systems

Author

Ling Shi, Yuzhe Li, Subhrakanti Dey, Daniel E. Quevedo, Li, Yuzhe, Quevedo, Daniel E, Dey, Subhrakanti, and Shi, Ling

Subjects
0209 industrial biotechnology, Schedule, Computer Networks and Communications, Computer science, Acknowledgement, 02 engineering and technology, security, Computer security, computer.software_genre, schedules, 020901 industrial engineering & automation, communication system security, 0202 electrical engineering, electronic engineering, information engineering, Wireless, state estimation, wireless sensor networks, business.industry, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, Cyber-physical system, 020206 networking & telecommunications, Engineering, Electrical & Electronic, wireless communication, Key distribution in wireless sensor networks, Signal Processing, State (computer science), business, Wireless sensor network, computer, Game theory, Information Systems, Computer network
Abstract

A class of malicious attacks against remote state estimation in cyber-physical systems is considered. A sensor adopts an acknowledgement (ACK)-based online power schedule to improve the remote state estimation performance under limited resources. To launch malicious attacks, the attacker can modify the ACKs from the remote estimator and convey fake information to the sensor, thereby misleading the sensor with subsequent performance degradation. One feasible attack pattern is proposed and the corresponding effect on the estimation performance is derived analytically. Due to the ACKs being unreliable, the sensor needs to decide at each instant, whether to trust the ACK information or not and adapt the transmission schedule accordingly. In the meanwhile, there is also a tradeoff for the attacker between attacking and not attacking when the modification of ACKs is costly. To investigate the optimal strategies for both the sensor and the attacker, a game-theoretic framework is built and the equilibrium for both sides is studied. Refereed/Peer-reviewed

Published
2017

6. SINR-Based DoS Attack on Remote State Estimation: A Game-Theoretic Approach

Author

Ling Shi, Yuzhe Li, Subhrakanti Dey, Daniel E. Quevedo, Li, Yuzhe, Quevedo, Daniel E, Dey, Subhrakanti, and Shi, Ling

Subjects
game theory, 0209 industrial biotechnology, Mathematical optimization, Control and Optimization, Computer Networks and Communications, Computer science, Markov process, Denial-of-service attack, security, 02 engineering and technology, cyber-physical systems, Interference (wave propagation), symbols.namesake, 020901 industrial engineering & automation, Signal-to-noise ratio, 0202 electrical engineering, electronic engineering, information engineering, Wireless network, 020208 electrical & electronic engineering, remote state estimation, Process (computing), Estimator, wireless sensors, Control and Systems Engineering, Signal Processing, symbols, State (computer science)
Abstract

We consider remote state estimation of cyber physical systems (CPS) under signal-to-interference-plus-noise ratio (SINR)-based denial-of-service (DoS) attacks. A sensors ends its local estimate to a remote estimator through a wireless network that may suffer interference from an attacker. Both the sensor and the attacker have energy constraints. We first study an associated two-player game when multiple power levels are available. Then we build a Markov game framework to model the interactive decision-making process based on the current state and information collected from previous time steps. To solve the associated optimality (Bellman) equations, a modified Nash Q learning algorithm is applied to obtain the optimal solutions.Numerical examples and simulations are provided to demonstrate our results. Refereed/Peer-reviewed

Published
2017

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