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A Game Approach for Defending System Security from an Attacker

IFAC-PapersOnLine 2023年第2期56卷 1710-1715页

作者： Yueyue Xu Xiaoming Hu Zhixin Liu Han Zhang Lin Wang Department of Automation Shanghai Jiao Tong University Shanghai 200240 China KTH Royal Institute of Technology Stockholm 10044 Sweden Key Laboratory of Systems and Control Academy of Mathematics and Systems Science CAS Beijing 100190 China

In this paper, a system security problem is studied based on a two-person non-cooperative dynamic game. Security of the system is regarded in the context of observability. Namely a system is secure if it is not observable. Both the defender and attacker are assumed to have means to modify the dimension of unobservable subspace, which is set as the value function. The strategies and algorithms to minimize or maximize the value function are given respectively. Finally, examples are provided to demonstrate the effectiveness of the proposed algorithms and show some interesting game results, including accumulation mode, loop mode and locked mode.

关键词： Linear systems dynamic game unobservable subspace relative degree V∗ space

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Kernel-Based Regularized Continuous-Time System Identification from Sampled Data

Kernel-Based Regularized Continuous-Time System Identificati...

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IEEE Conference on Decision and control

作者： Xiaozhu Fang Biqiang Mu Tianshi Chen School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China Key Laboratory of Systems and Control of CAS Institute of Systems Science Academy of Mathematics and System Science Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

The identification of continuous-time (CT) systems from discrete-time (DT) input and output signals, i.e., the sampled data, has received considerable attention for half a century. The state-of-the-art methods are parametric methods and thus subject to the typical issues of parametric methods. In the last decade, a major advance in system identification is the so-called kernel-based regularization method (KRM), which is free of the issues of parametric methods. It is interesting to test the potential of KRM on CT system identification. However, very few results have been reported, mainly because the estimators have no closed forms for general CT input signals, except for some very special cases. In this paper, we show for KRM that the estimators have closed forms when the DT input signal has the typical intersample behavior, i.e., zero-order hold or band-limited, and this paves the way for the application of KRM for CT system identification. Numerical Monte Carlo simulations show that the proposed method is more robust than the state-of-the-art methods and more accurate when the sample size is small.

关键词： Accuracy Monte Carlo methods Numerical simulation Robustness System identification Standards

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Protection of Access Pattern 7

Protection of Access Pattern

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7th International Conference on Computer Science and Artificial Intelligence, CSAI 2023

作者： Gao, Biao Jia, Shijie Yin, Peng Zhang, Xueying State Key Laboratory of Information Security Institute of Information Engineering Cas School of Cyber Security University of Chinese Academy of Sciences Beijing China Defence Industry Secrecy Examination and Certification Center School of Cyber Security University of Chinese Academy of Sciences Beijing China China Industrial Control Systems Cyber Emergency Response Team Beijing China

ISBN: (纸本)9798400708688

Encryption is insufficient to ensure the system security because the access patterns of user will still reflect the information about the data and serve as an indicator for adversary to infer the sensitive information. We conclude the related work on the access pattern protection to provide a thorough literature review of history independence and oblivious random access machine, which address the issues of static and dynamic access pattern observations respectively. © 2023 Owner/Author.

关键词： Cryptography

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Modeling and analysis of an underwater biomimetic vehicle-manipulator system

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Science China(Information Sciences) 2022年第3期65卷 255-257页

作者： Xuejian BAI Yu WANG Shuo WANG Rui WANG Min TAN Wei WANG School of Artificial Intelligence University of Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences CAS Center for Excellence in Brain Science and Intelligence Technology School of Control Science and Engineering Shandong University

In recent years, underwater vehicle-manipulator systems(UVMSs) have captured researchers' attention. Inspired by fish, bionic mechanisms were introduced into a *** underwater biomimetic vehicle-manipulator system(UBVMS) is actuated by two symmetrically arranged biomimetic undulatory fin propulsors [1]. Based on the UBVMS, some topics have been researched, such as freefloating autonomous operation [2, 3], three-dimensional helical path following [4], and underwater video processing [5].

关键词： underwater biomimetic vehicle underwater robots underwater vehicle-manipulator system biomimetic robots hydrodynamic modeling

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Kernel-Based Regularized Continuous-Time System Identification from Sampled Data

arXiv

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arXiv 2024年

作者： Fang, Xiaozhu Mu, Biqiang Chen, Tianshi School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China The Key Laboratory of Systems and Control of CAS Institute of Systems Science Academy of Mathematics and System Science Chinese Academy of Sciences Beijing100190 China

The identification of continuous-time (CT) systems from discrete-time (DT) input and output signals, i.e., the sampled data, has received considerable attention for half a century. The state-of-the-art methods are parametric methods and thus subject to the typical issues of parametric methods. In the last decade, a major advance in system identification is the so-called kernel-based regularization method (KRM), which is free of the issues of parametric methods. It is interesting to test the potential of KRM on CT system identification. However, very few results have been reported, mainly because the estimators of KRM have no closed forms for general CT input signals, except for some very special cases. In this paper, we show for KRM that the estimators have closed forms when the DT input signal has the typical intersample behavior, i.e., zero-order hold or band-limited, and this paves the way for the application of KRM for CT system identification. Numerical simulations show that the proposed method is more robust than the state-of-the-art methods and more accurate when the sample size is small. © 2024, CC BY.

关键词： Continuous time systems

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Adaptive Fusional Localization for Robot Fish Based on Dynamic-weight Fuzzy Inference

Adaptive Fusional Localization for Robot Fish Based on Dynam...

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2021 China Automation Congress, CAC 2021

作者： Fu, Yuzhuo Liao, Xiaocun Lu, Ben Zou, Qianqian Zhang, Zhuoliang Ou, Yarning Zhou, Chao State Key Laboratory of Management and Control for Complex Systems Institute of Automation CAS Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781665426473

Accurate localization of robots in a specific environment often requires the cooperation of multiple sensors, and how to establish a more general data fusion model is always a difficult problem. For the localization of robot fish in an indoor pool environment, this paper proposes an adaptive fusional algorithm based on fuzzy inference of dynamic weights. This paper firstly constructs a confidence probability table of sensors' signals based on the calibration data sets of BLE and UWB nodes at different distances, as the basis for updating the weights of the BLE or UWB nodes;secondly, the data obtained by each node in a single sampling period in the robot fish movement is vectorized to form a judgment matrix, and then the estimated distance is obtained by fuzzy inference together with the sensor weight;finally, the coordinates are calculated by the four-point positioning method. In this paper, more than 40 sets of experiments have been carried out with a simplified carangidae-like robot fish. The results show that the average positioning error is about 0.189m, which is 88.3% and 31.8% lower than that of using BLE only and using UWB only. In this paper, the fusional positioning method based on statistics combines the advantages of different sensors to reduce the data scale and achieve data denoising while fusing sensor data, which provides a reference for indoor positioning of robot fish and multi-sensor data fusion. © 2021 IEEE

关键词： Fuzzy inference

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A new anterograde trans-synaptic tracer based on Sindbis virus

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Neural Regeneration Research 2022年第12期17卷 2761-2764页

作者： Xiang-Wei Shi Fan Jia Pei Lyu Fu-Qiang Xu State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Key Laboratory of Magnetic Resonance in Biological SystemsWuhan Center for Magnetic ResonanceInnovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhanHubei ProvinceChina Guangdong Provincial Key Laboratory of Brain Connectome and Behavior CAS Key Laboratory of Brain Connectome and Manipulationthe Brain Cognition and Brain Disease Institute(BCBDI)Translational Research Center for the Nervous System(TRCNS)Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research InstitutionsShenzhenGuangdong ProvinceChina NMPA Key Laboratory for Research and Evaluation of Viral Vector Technology in Cell and Gene Therapy Medicinal Products Key Laboratory of Quality Control Technology for Virus-Based TherapeuticsGuangdong Provincial Medical Products AdministrationShenzhen Key Laboratory of Viral Vectors for BiomedicineShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenGuangdong ProvinceChina University of Chinese Academy of Sciences BeijingChina Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhanHubei ProvinceChina

Mapping neural circuits is critical for understanding the structure and function of the nervous *** viruses are a valuable tool for tracing neural ***,current tracers do not fully meet the needs for this approach because of various drawbacks,such as toxicity and characteristics that are difficult to ***,there is an urgent need to develop a new tracer with low toxicity and that allows for long-term *** this study,we constructed an engineered Sindbis virus(SINV)expressing enhanced green fluorescent protein(EGFP)reporter gene(SINV-EGFP)and found that it had no significant difference in biological characterization compared with the wild-type Sindbis virus in BHK-21 cells and neurons in *** injected the virus into the visual circuit of mouse brain and found that the virus infected neurons in the local injected site and anterogradely spread in the neural *** the efficiency of transmission was limited,the findings demonstrate that SINV can be used as a new anterograde tracer to map neural circuits in mouse brain and that it spreads exclusively in the anterograde ***,use of SINV in mouse brain research will provide longer time windows for circuit tracing than is possible with herpes simplex virus and vesicular stomatitis virus tracers.

关键词： anterograde lateral geniculate nucleus mouse brains neural circuit neurons retina Sindbis virus superior colliculus synapse tracer

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Application of machine learning method in optical molecular imaging: a review

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Science China(Information Sciences) 2020年第1期63卷 5-20页

作者： Yu AN Hui MENG Yuan GAO Tong TONG Chong ZHANG Kun WANG Jie TIAN CAS Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular ImagingThe State Key Laboratory of Management and Control for Complex SystemsInstitute of Automation Chinese Academy of Sciences Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of MedicineBeihang University University of Chinese Academy of Sciences

Optical molecular imaging(OMI) is an imaging technology that uses an optical signal, such as near-infrared light, to detect biological tissue in organisms. Because of its specific and sensitive imaging performance, it is applied in both preclinical research and clinical surgery. However, it requires heavy data analysis and a complex mathematical model of tomographic imaging. In recent years, machine learning(ML)-based artificial intelligence has been used in different fields because of its ability to perform powerful data processing. Its analytical capability for processing complex and large data provides a feasible scheme for the requirement of OMI. In this paper, we review ML-based methods applied in different OMI modalities.

关键词： optical molecular imaging machine learning artificial intelligence

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Tunable and Functional Ionic Liquids Embedded Hyper-Crosslinked Polymers as H2o-Tolerant Adsorbents for Highly Efficient Gaseous Toluene Capture

SSRN

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SSRN 2024年

作者： Nie, Xiongfei Qiu, Xinjie Zhang, Ruina Ke, Quanli Liu, Huayan Zhang, Xiangping Lu, Hanfeng Cui, Guokai Zhang, Suojiang Innovation Team of Air Pollution Control Institute of Catalytic Reaction Engineering State Key Laboratory Breeding Base of Green Chemistry Synthesis Technology College of Chemical Engineering Zhejiang University of Technology Hangzhou310014 China Beijing Key Laboratory of Ionic Liquids Clean Process CAS Key Laboratory of Green Process and Engineering State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China

Developing advanced sorbents for efficient aromatic VOCs sorption from humid conditions are highly desired. In this work, a series of tunable and functional ionic liquids embedded hyper-crosslinked polymers (ILHCPs) containing different structures of anion-functional ionic liquids (ILs) with 1,4-dichloroxylene (DCX) as the crosslinker were designed and prepared for highly efficient gaseous toluene adsorption under humidity. These ILHCPs could achieve high surface area (600~900 m2 g−1), high micropore volume (0.1~0.3 cm3 g−1), small average pore size (4~5 nm), and large water contact angle (up to 110°) through tuning the anion structures and the initial IL:DCX molar ratio. Gaseous toluene adsorption isotherms on typical ILHCPs were tested under 298, 308, and 318 K, and a dual-site Langmuir-Freundlich (DSLF) model was used for well describing adsorption isotherms, which can be divided into two contributions for site I and site II. The isosteric heats of gaseous toluene adsorption were calculated. Furthermore, toluene adsorption under different humidity conditions were also tested. Compared with DCX-based self-condensed HCP, toluene adsorption capacity of ILHCPs remained steadily (270 mg g−1) even under 80% humidity. To our best knowledge, this is the first example of tuning functional ILHCPs for efficient H2O-tolerant gaseous toluene adsorption. The method may also open a door to achieving high adsorption efficiency of other volatile organic compounds by functional IL-based porous materials. © 2024, The Authors. All rights reserved.

关键词： Gas adsorption

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Perception for Coupler Rod of Freight Train Based on Image and Point Clouds

Perception for Coupler Rod of Freight Train Based on Image a...

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2022 Chinese Automation Congress, CAC 2022

作者： Guo, Renjie Feng, Jun Yang, Huachang Luan, Dejie Yang, Guodong Li, En Institute of Automation CAS State Key Laboratory of Management and Control for Complex Systems Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China China Academy of Railway Sciences Corporation Limited Signal & Communication Research Institute Beijing100081 China

ISBN: (纸本)9781665465335

In the construction of automated marshaling yards, the automatic uncoupling operation of freight trains has always been the research and development direction. The coupler rod is the operation object of the uncoupling operation. The identification of coupler rod type and estimating position and posture are the prerequisites to realizing automatic uncoupling operation. In this paper, we propose a perception method of coupler rod by RGB image combined with the point cloud. We use an RGBD camera to synchronously collect frame-aligned RGB and depth images and generate point cloud data with colors according to the mapping relationship. Then, we use the YOLOv5 neural network to detect the collected RGB images and recognize the type of coupler rod in the image. Clear clutter in the point cloud and the bounding box is mapped to a spatial coordinate system for straight-through filtering of the point cloud. We use RANSAC for coarse registration and ICP for fine registration. The result of registration is carried out with the lower sampling point cloud model to achieve the registration of the coupler rod. Experiments show that this method can effectively segment the point cloud of the region of interest with high robustness. © 2022 IEEE.

关键词： Data fusion

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