Developing graphical detection techniques for maintaining state estimation integrity against false data injection attack in integrated electric cyber-physical system

2020 ◽  
Vol 105 ◽  
pp. 101705 ◽  
Author(s):  
Yuancheng Li ◽  
Yuanyuan Wang
Keyword(s):  
State Estimation ◽  
Physical System ◽  
Cyber Physical System ◽  
Detection Techniques ◽  
False Data Injection ◽  
False Data Injection Attack

Research on cyber-physical system control strategy under false data injection attack perception

2022 ◽  
pp. 014233122110693
Author(s):  
Zhiwen Wang ◽  
Bin Zhang ◽  
Xiangnan Xu ◽  
Usman ◽  
Long Li
Keyword(s):  
Control Strategy ◽  
Physical System ◽  
Sufficient Conditions ◽  
Switched System ◽  
Lyapunov Methods ◽  
Control Technique ◽  
Cyber Physical System ◽  
Time Data ◽  
False Data Injection ◽  
Injection Attacks

This paper investigates the security control problem of the cyber-physical system under false data injection attacks. A model predictive switching control strategy based on attack perception is proposed to compensate for the untrusted sequence of data caused by false data injection attacks. First, the binary attack detector is applied whether the system has suffered the attack. If the attack occurs, multistep correction is carried out for the future data according to the previous time data, and the waiting period [Formula: see text] is set. The input and output sequence of the controller is reconstructed, and the system is modeled as a constant time-delay switched system. Subsequently, the Lyapunov methods and average-dwell time are combined to provide sufficient conditions for the asymptotical stability of closed-loop switched system. Finally, the simulation of the networked first-order inverted pendulum model reveals that the control technique can efficiently suppress the influence of the attacks.

scholarly journals Net Load Redistribution Attacks on Nodal Voltage Magnitude Estimation in AC Distribution Networks.pdf

2020 ◽  
Author(s):  
hang zhang ◽  
Bo Liu ◽  
Hongyu Wu
Keyword(s):  
State Estimation ◽  
Distribution System ◽  
Local Network ◽  
Network Information ◽  
False Data Injection ◽  
Load Redistribution ◽  
System Operator ◽  
False Data Injection Attack ◽  
Nodal Voltage ◽  
Net Load

This paper presents a false data injection attack against AC state estimation in distribution system. Such attack is called net local load redistribution attacks (NRLA) which is aimed at misleading the distribution system operator to observe illusory under-voltage issues in the AC state estimation. The attack vector is constructed with only local network information.<br>

scholarly journals Net Load Redistribution Attacks on Nodal Voltage Magnitude Estimation in AC Distribution Networks.pdf

2020 ◽  
Author(s):  
hang zhang ◽  
Bo Liu ◽  
Hongyu Wu
Keyword(s):  
State Estimation ◽  
Distribution System ◽  
Local Network ◽  
Network Information ◽  
False Data Injection ◽  
Load Redistribution ◽  
System Operator ◽  
False Data Injection Attack ◽  
Nodal Voltage ◽  
Net Load

This paper presents a false data injection attack against AC state estimation in distribution system. Such attack is called net local load redistribution attacks (NRLA) which is aimed at misleading the distribution system operator to observe illusory under-voltage issues in the AC state estimation. The attack vector is constructed with only local network information.<br>

scholarly journals Secure State Estimation for Motion Monitoring of Intelligent Connected Vehicle Systems

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1253
Author(s):  
Xiulan Song ◽  
Xiaoxin Lou ◽  
Junwei Zhu ◽  
Defeng He
Keyword(s):  
State Estimation ◽  
Estimation Method ◽  
Estimation Problem ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
Monitoring Networks ◽  
Cruise Control ◽  
False Data Injection ◽  
Vehicle Systems ◽  
False Data Injection Attack

This paper considers the state estimation problem of intelligent connected vehicle systems under the false data injection attack in wireless monitoring networks. We propose a new secure state estimation method to reconstruct the motion states of the connected vehicles equipped with cooperative adaptive cruise control (CACC) systems. First, the set of CACC models combined with Proportion-Differentiation (PD) controllers are used to represent the longitudinal dynamics of the intelligent connected vehicle systems. Then the notion of sparseness is employed to model the false data injection attack of the wireless networks of the monitoring platform. According to the corrupted data of the vehicles’ states, the compressed sensing principle is used to describe the secure state estimation problem of the connected vehicles. Moreover, the L1 norm optimization problem is solved to reconstruct the motion states of the vehicles based on the orthogonaldecomposition. Finally, the simulation experiments verify that the proposed method can effectively reconstruct the motion states of vehicles for remote monitoring of the intelligent connected vehicle system.

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