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Side Information-Based Stealthy False Data Injection Attacks Against Multi-Sensor Remote Estimation

IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1054-1056页

作者： Haibin Guo Zhong-Hua Pang Chao Li the Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of TechnologyBeijing 100144China

Dear Editor,This letter investigates a novel stealthy false data injection(FDI)attack scheme based on side information to deteriorate the multi-sensor estimation performance of cyber-physical systems(CPSs).Compared with most existing works depending on the full system knowledge,this attack scheme is only related to attackers'sensor and physical process *** design principle of the attack signal is derived to diverge the system estimation ***,it is proven that the proposed attack scheme can successfully bypass the residual-based ***,all theoretical results are verified by numerical simulation.

关键词： estimation scheme system

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Prediction-Based State Estimation and Compensation Control for Networked Systems With Communication Constraints and DoS Attacks

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2352-2354页

作者： Zhong-Hua Pang Qian Cao Haibin Guo Zhe Dong IEEE the Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of Technology

Dear Editor,This letter investigates the output tracking control issue of networked control systems(NCSs)with communication constraints and denial-of-service(DoS)attacks in the sensor-to-controller channel,both of whi... 详细信息

关键词： DoS service network

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Residual-Based False Data Injection Attacks Against Multi-Sensor Estimation Systems

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1181-1191页

作者： Haibin Guo Jian Sun Zhong-Hua Pang the National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China the Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China the Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of TechnologyBeijing 100144China

This paper investigates the security issue of multisensor remote estimation *** optimal stealthy false data injection(FDI)attack scheme based on historical and current residuals,which only tampers with the measurement residuals of partial sensors due to limited attack resources,is proposed to maximally degrade system estimation *** attack stealthiness condition is given,and then the estimation error covariance in compromised state is derived to quantify the system performance under *** optimal attack strategy is obtained by solving several convex optimization problems which maximize the trace of the compromised estimation error covariance subject to the stealthiness ***,due to the constraint of attack resources,the selection principle of the attacked sensor is provided to determine which sensor is attacked so as to hold the most impact on system ***,simulation results are presented to verify the theoretical analysis.

关键词： Cyber-physical systems(CPSs) false data injection(FDI)attacks remote state estimation stealthy attacks

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Analysis of Stealthy False Data Injection Attacks Against Networked Control Systems:Three Case Studies

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Journal of Systems Science & Complexity 2023年第4期36卷 1407-1422页

作者： PANG Zhonghua FU Yuan GUO Haibin SUN Jian Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of TechnologyBeijing 100144China National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China

This paper mainly investigates the security problem of a networked control system based on a Kalman filter.A false data injection attack scheme is proposed to only tamper the measurement output,and its stealthiness and effects on system performance are analyzed under three cases of system knowledge held by an attacker and a ***,it is derived that the proposed attack scheme is stealthy for a residual-based detector when the attacker and the defender hold the same accurate system ***,it is proven that the proposed attack scheme is still stealthy even if the defender actively modifies the Kalman filter gain so as to make it different from that of the ***,the stealthiness condition of the proposed attack scheme based on an inaccurate model is ***,for each case,the instability conditions of the closed-loop system under attack are ***,simulation results are provided to test the proposed attack scheme.

关键词： False data injection attack networked control systems(NCSs) stability stealthiness

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Embodied intelligence in RO/RO logistic terminal:autonomous intelligent transportation robot architecture

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Science China(Information Sciences) 2025年第5期68卷 153-169页

作者： Yongkang XU Runjiao BAO Lin ZHANG Junzheng WANG Shoukun WANG School of Automation Beijing Institute of Technology National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology

In this paper, an autonomous intelligent transportation robot equipped with intelligent perception and autonomous planning modules is proposed to meet the requirements of roll-on/roll-off(RO/RO) logistics terminals for the autonomous transportation of various types of finished vehicles. Based on the robot operating system(ROS) framework and a modular design approach, the robot integrates several key components, including a visual perception module, an autonomous planning module, a motion control module, an execution module, and an energy module. First, an improved convex hull algorithm efficiently extracts point cloud data, enhancing the efficiency of point cloud processing and addressing the issue of excessive target data. Three different evaluation methods were employed to determine the optimal bounding box of the target vehicle and to obtain its pose state. Second, improved proximal policy optimization(PPO) and generalized advantage estimation(GAE) algorithms, which are utilized in this paper, were implemented to autonomously plan collisionfree trajectories for robots, facilitating their movement from an initial position to the target transportation location, and subsequently to the final placement position. Finally, physical experiments confirmed that the robot effectively mimics the three fundamental components of humanoid functionality: perception, cognition, and action, thus enabling autonomous and intelligent handling of complex vehicle transportation tasks. These demonstrations validate the feasibility and effectiveness of the proposed robot.

关键词： embodied intelligence transportation robot RO/RO logistic terminal detection autonomous planning

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Deep reinforcement learning for optimal denial-of-service attacks scheduling

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Science China(Information Sciences) 2022年第6期65卷 98-106页

作者： Fangyuan HOU Jian SUN Qiuling YANG Zhonghua PANG State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of Technology

We consider an optimal denial-of-service(DoS) attack scheduling problem of N independent linear time-invariant processes, where sensors have limited computational capability. Sensors transmit measurements to the remote estimator via a communication channel that is exposed to DoS attackers. However,due to limited energy, an attacker can only attack a subset of sensors at each time step. To maximally degrade the estimation performance, a DoS attacker needs to determine which sensors to attack at each time step. In this context, a deep reinforcement learning(DRL) algorithm, which combines Q-learning with a deep neural network, is introduced to solve the Markov decision process(MDP). The DoS attack scheduling optimization problem is formulated as an MDP that is solved by the DRL algorithm. A numerical example is provided to illustrate the efficiency of the optimal DoS attack scheduling scheme using the DRL algorithm.

关键词： optimal denial-of-service attack scheduling optimization limited energy deep reinforcement learning

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Data-Driven Adaptive Predictive Control Method With Autotuned Weighting Factor for Nonlinear Systems Using Triangular Dynamic Linearization

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1880-1882页

作者： Zhong-Hua Pang Yumo Zhang Xueyuan Sun Shengnan Gao Guo-Ping Liu Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of TechnologyBeijing 100144China School of Data Science Capital University of Economics and BusinessBeijing 100070China Center for Control Science and Technology Southern University of Science and TechnologyShenzhen 518055China

Dear Editor,In this letter,a novel data-driven adaptive predictive control method is proposed using the triangular dynamic linearization *** proposed method only contains one time-varying parameter with explicit physical meaning,which can prevent severe deviation in parameter ***,a triangular dynamic linearization(TDL)data model is employed to predict future system outputs,and then to correct inaccurate predictive outputs,a feedback regulator is *** autotuned weighing factor is introduced to alleviate the computational burden in practical applications and further improve output tracking ***-loop stability conditions are derived by rigorous *** results are provided to demonstrate the efficacy of the proposed method.

关键词： estimation technique method

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Output Tracking Control for Networked Control Systems with Random Communication Constraints and Model Mismatch 42

Output Tracking Control for Networked Control Systems with R...

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42nd Chinese Control Conference, CCC 2023

作者： Li, Gang Yu, Xue-Sheng Du, Tao Pang, Zhong-Hua Xue, Tonglai North China University of Technology Key Laboratory of Fieldbus Technology and Automation of Beijing Beijing100144 China

ISBN: (纸本)9789887581543

This paper addresses the problem of output tracking control for networked control systems (NCSs) with model mismatch and random communication constraints. In order to actively compensate random communication constraints and reduce the impact of model mismatch on system output, a novel networked predictive control scheme with correction item is proposed, which consists of data buffer, prediction generator and controller. The sufficient and necessary condition for the stability of the closed-loop system are derived. Using the proposed control scheme, the simulation results are presented to show that the desired output tracking performance can be achieved. © 2023 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Networked control systems

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MC-NeRF: Multi-Camera Neural Radiance Fields for Multi-Camera Image Acquisition Systems

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IEEE Transactions on Visualization and Computer Graphics 2025年第5期31卷 2725-2735页

作者： Gao, Yu Su, Lutong Liang, Hao Yue, Yufeng Yang, Yi Fu, Mengyin Beijing Institute of Technology School of Automation Beijing China Beijing Institute of Technology National Key Lab of Autonomous Intelligent Unmanned Systems Beijing China

Neural Radiance Fields (NeRF) use multi-view images for 3D scene representation, demonstrating remarkable performance. As one of the primary sources of multi-view images, multi-camera systems encounter challenges such as varying intrinsic parameters and frequent pose changes. Most previous NeRF-based methods assume a unique camera and rarely consider multi-camera scenarios. Besides, some NeRF methods that can optimize intrinsic and extrinsic parameters still remain susceptible to suboptimal solutions when these parameters are poor initialized. In this paper, we propose MC-NeRF, a method for joint optimization of both intrinsic and extrinsic parameters alongside NeRF, allowing individual camera parameters for each image. First, we analyze the coupling issue that arises from the joint optimization between intrinsics and extrinsics, and propose a decoupling constraint utilizing auxiliary images. To further address the degenerate cases in the decoupling process, we introduce an efficient auxiliary image acquisition scheme to mitigate these effects. Furthermore, recognizing that most existing datasets are designed for a unique camera, we provided a new dataset that includes both simulated data and real-world data. Experiments demonstrate the effectiveness of our method in scenarios where each image corresponds to different camera parameters. Specifically, our approach outperforms the baselines favorably in terms of intrinsics estimation, extrinsics estimation, scale estimation, and rendering quality. The Code and supplementary materials are available at https://***/MC-NeRF. © 1995-2012 IEEE.

关键词： Volume rendering

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Inexact proximal gradient algorithm with random reshuffling for nonsmooth optimization

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Science China(Information Sciences) 2025年第1期68卷 219-237页

作者： Xia JIANG Yanyan FANG Xianlin ZENG Jian SUN Jie CHEN National Key Lab of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center School of Electronic and Information Engineering Tongji University

Proximal gradient algorithms are popularly implemented to achieve convex optimization with nonsmooth regularization. Obtaining the exact solution of the proximal operator for nonsmooth regularization is challenging because errors exist in the computation of the gradient; consequently, the design and application of inexact proximal gradient algorithms have attracted considerable attention from researchers. This paper proposes computationally efficient basic and inexact proximal gradient descent algorithms with random reshuffling. The proposed stochastic algorithms take randomly reshuffled data to perform successive gradient descents and implement only one proximal operator after all data pass through. We prove the convergence results of the proposed proximal gradient algorithms under the sampling-without-replacement reshuffling *** computational errors exist in gradients and proximal operations, the proposed inexact proximal gradient algorithms can converge to an optimal solution neighborhood. Finally, we apply the proposed algorithms to compressed sensing and compare their efficiency with some popular algorithms.

关键词： proximal operator random reshuffling inexact computation compressed sensing nonsmooth optimization

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