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.

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>

Sensor Fault Diagnosis of Connected Vehicles Under Imperfect Communication Network

2016 ◽  
Author(s):  
Zoleikha Abdollahi Biron ◽  
Satadru Dey ◽  
Pierluigi Pisu
Keyword(s):  
Communication Network ◽  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
Cruise Control ◽  
Vehicle System ◽  
Safety And Reliability ◽  
The Individual ◽  
Control Management

Connected vehicles are one of the promising technologies for future Intelligent Transportation Systems (ITS). Despite being the potentially beneficial in creating an efficient, sustainable and green transportation system, connected vehicles presents a set of specific challenges from safety and reliability standpoint. The first challenge arises from the information lost due to unreliable communication network which affects the control/management system of the individual vehicles and the overall system. Secondly, faulty sensors can affect the individual vehicle’s safe operation and in turn will create a potentially unsafe node in the vehicular network. Therefore, it is of utmost importance to take these issues into consideration while designing the control/management algorithms of the individual vehicles as a part of connected vehicle system. In this paper, we consider a connected vehicle system under Co-operative Adaptive Cruise Control (CACC) and propose a diagnostic scheme that deals with these aforementioned challenges. The effectiveness of the overall diagnostic scheme is verified via simulation studies.

Adaptive state estimation for cyber physical systems under sparse attacks

2018 ◽  
Vol 41 (6) ◽  
pp. 1571-1579 ◽  
Author(s):  
Hao Zhang ◽  
Chen Peng ◽  
Hongtao Sun ◽  
Dajun Du
Keyword(s):  
State Estimation ◽  
Adaptive Estimation ◽  
Computing Time ◽  
Estimation Method ◽  
Cyber Physical Systems ◽  
Estimation Problem ◽  
Step Size ◽  
Estimation Errors ◽  
Physical Systems ◽  
Dynamic Estimation

This paper investigates the state estimation problem for cyber physical systems under sparse attacks. Firstly, the fundamental state estimation problem is transferred to an optimization problem with a unique solution. Secondly, an adaptive estimation method for sparse attacks is proposed, which convergence property is well proved. The advantage of proposed method is that the step-size can be adaptively adjusted based on the dynamic estimation errors. Therefore, the computing time is less than some existing methods while guaranteeing the desired performance. Then, a suitable state feedback is designed to improve the computing speed while enhancing the resiliency for the destroyed system. Finally, the speed performance and accuracy of proposed algorithm are verified by two numerical examples.

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