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Detection of Perfect Stealthy Attacks on Cyber-Physical systems Subject to Measurement Quantizations: A Watermark-Based Strategy

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 114-125页

作者： Yu-Ang Wang Zidong Wang Lei Zou Bo Shen Hongli Dong the College of Information Science and Technology Donghua University the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of Education IEEE the College of Electrical Engineering and Automation Shandong University of Science and Technology the Department of Computer Science Brunel University London Uxbridge the Sanya Offshore Oil and Gas Research Institute Northeast Petroleum University the Artificial Intelligence Energy Research Institute Northeast Petroleum University Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University

In this paper, the attack detection problem is investigated for a class of closed-loop systems subjected to unknownbutbounded noises in the presence of stealthy attacks. The measurement outputs from the sensors are quantized before transmission.A specific type of perfect stealthy attack, which meets certain rather stringent conditions, is taken into account. Such attacks could be injected by adversaries into both the sensor-toestimator and controller-to-actuator channels, with the aim of disrupting the normal data flow. For the purpose of defending against these perfect stealthy attacks, a novel scheme based on watermarks is developed. This scheme includes the injection of watermarks(applied to data prior to quantization) and the recovery of data(implemented before the data reaches the estimator).The watermark-based scheme is designed to be both timevarying and hidden from adversaries through incorporating a time-varying and bounded watermark signal. Subsequently, a watermark-based attack detection strategy is proposed which thoroughly considers the characteristics of perfect stealthy attacks,thereby ensuring that an alarm is activated upon the occurrence of such attacks. An example is provided to demonstrate the efficacy of the proposed mechanism for detecting attacks.

关键词： Attack detection cyber-physical systems (CPSs) perfect stealthy attacks watermark-based strategy

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Connectivity in the era of the (I)IoT: about security, features and limiting factors of reconfigurable intelligent surfaces

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Discover Internet of Things 2023年第1期3卷 16页

作者： Lipps, Christoph Herbst, Jan Klingel, Steffen Franke, Lars Wolff, Alexander Rüb, Matthias Reddy, Rekha Rahm, Marco Schotten, Hans Dieter Intelligent Networks Research Group German Research Center for Artificial Intelligence Kaiserslautern67663 Germany Institute for Wireless Communication and Radio Positioning RPTU Kaiserslautern-Landau Kaiserslautern67663 Germany Department of Electrical and Computer Engineering Research Center OPTIMAS RPTU Kaiserslautern-Landau Kaiserslautern67663 Germany

What are the key drivers of the (Industrial) Internet of Things ((I)IoT)? Alongside the interconnection of the various devices, sensors, and actuators, it is above all the data collected and transmitted that is of particular significance, the (I)IoT itself is the source and recipient of various types of data. Within this, there are two main aspects that need to be considered: (i) the transmission of data with appropriate latency and reliability requirements, and (ii) the safeguarding of this data. Both requirements are taken into account during the development of the Sixth Generation (6G) Wireless systems. This is conceived to deliver higher data rates, reduced cost deployment, and enhanced reliability while providing universal connectivity. Hence, to assist such a vast network domain, (new) 6G-enabling technologies are developed, which include Reconfigurable intelligent Surfaces (RISs), that are capable of modifying and reconfiguring the wireless propagation channels. This work describes concepts on how security, in particular Physical Layer Security (PhySec) methods, can be supported by RISs. Furthermore, an effective impedance surface model is presented, allowing efficient simulation of beamsplitting and shaping properties of RISs. Finally, the applicability of the use cases is mentioned, with a particular focus on Visible Light Communication (VLC). © The Author(s) 2023.

关键词： Internet of things

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A Bi-population Cooperative Optimization Algorithm Assisted by an Autoencoder for Medium-scale Expensive Problems

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IEEE/CAA Journal of Automatica Sinica 2022年第11期9卷 1952-1966页

作者： Meiji Cui Li Li MengChu Zhou Jiankai Li Abdullah Abusorrah Khaled Sedraoui IEEE the School of Intelligent Manufacturing Nanjing University of Science and TechnologyNanjing 210094China the Department of Electronics and Information Engineering Tongji UniversityShanghai 201804China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of Engineeringand K.A.CARE Energy Research and Innovation CenterKing Abdulaziz UniversityJeddah 21589Saudi Arabia

This study presents an autoencoder-embedded optimization(AEO)algorithm which involves a bi-population cooperative strategy for medium-scale expensive problems(MEPs).A huge search space can be compressed to an informative lowdimensional space by using an autoencoder as a dimension reduction *** search operation conducted in this low space facilitates the population with fast convergence towards the *** strike the balance between exploration and exploitation during optimization,two phases of a tailored teaching-learning-based optimization(TTLBO)are adopted to coevolve solutions in a distributed fashion,wherein one is assisted by an autoencoder and the other undergoes a regular evolutionary ***,a dynamic size adjustment scheme according to problem dimension and evolutionary progress is proposed to promote information exchange between these two phases and accelerate evolutionary convergence *** proposed algorithm is validated by testing benchmark functions with dimensions varying from 50 to *** indicated in our experiments,TTLBO is suitable for dealing with medium-scale problems and thus incorporated into the AEO framework as a base *** with the state-of-the-art algorithms for MEPs,AEO shows extraordinarily high efficiency for these challenging problems,t hus opening new directions for various evolutionary algorithms under AEO to tackle MEPs and greatly advancing the field of medium-scale computationally expensive optimization.

关键词： Autoencoder dimension reduction evolutionary algorithm medium-scale expensive problems teaching-learning-based optimization

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Optimizing One-Stage Object Detection for URLLC: A Two-Stage Pipeline with Oculi SPU 25

Optimizing One-Stage Object Detection for URLLC: A Two-Stage...

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Moghlebey, Adam Bou Moubayed, Abdallah Injadat, MohammadNoor Lebanese American University Electrical & Computer Engineering Department Byblos Lebanon King Fahd University of Petroleum & Minerals Computer Engineering Department Interdisciplinary Research Center for Intelligent Secure Systems Dhahran Saudi Arabia Zarqa University Data Science & Artificial Intelligence Department Zarqa Jordan University of Business and Technology Jeddah Saudi Arabia

ISBN: (纸本)9798331540012

Pedestrian-related accidents account for an estimated 20-25% of the approximately 1.19 million road fatalities occurring annually, highlighting the urgent need for enhanced detection systems in surveillance and smart transportation to mitigate such incidents. The escalating demand for Ultra-Reliable Low-Latency Communications (URLLC) in modern surveillance and transportation systems has become a solution to that problem but highlighted significant challenges in reducing inference times of machine learning models, particularly on constrained hardware. The maximum permissible latency for most vehicular applications ranges from 6 to 20 milliseconds based on the application. When tested on an 8GB RAM setup using the NTU, LLVIP, and VIRAT datasets, YOLOv8n achieved a minimum inference time of approximately 200 milliseconds per frame, making it unsuitable for URLLC applications despite 8GB RAM being an adequate hardware setup for edge devices. This research introduces a new two-stage pipeline that integrates Oculi's Sensing and Processing Unit (SPU) simulation with the YOLOv8n one-stage object detection model to enhance pedestrian detection, thereby addressing these challenges. By leveraging Regions of Interest (ROIs) generated by Oculi's SPU, our approach optimizes the input data for the YOLO model, substantially reducing computational overhead and thus making it suitable for URLLC applications. This integration can lead to a reduction in inference time by up to 93% in the tested frames when being compared to YOLOv8n pre-trained model. © 2024 IEEE.

关键词： Digital storage

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Contactless Interaction System Based on Facial Expression Recognition for Humanoid Piano Robot

Contactless Interaction System Based on Facial Expression Re...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Zhong, Ling Wang, Wen Zhu, Shiqiang Ji, Shanshan Zha, Changhai Wan, Minhong Gu, Jason Research Center for Intelligent Robotics Zhejiang Engineering Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Lab Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

With the wide application of service robots in people's daily life, people are not only satisfied with robots accomplishing tasks independently but also hope that robots can maintain sustainable interaction with human beings. Especially in the field of music, robots need to be equipped with intelligent cognitive skills in decision-making, so that the audience can enjoy immersive appreciation and emotional resonance in the robots performance. Visual perception and natural language understanding are essential for robots to establish human-robot friendly relationships. To enrich the interactive ability of music robots, we design a contactless interaction system based on facial expression recognition, which consists of four modules: voice wake-up, face detection, facial expression recognition, and music mapping. When people wake up the music robot with specific words, the robot will customize appropriate music to perform according to the recognition results of the FER module. As a final step, the interaction system has been successfully applied to the piano humanoid robot independently developed by our team. © 2022 IEEE.

关键词： Decision making

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MSMB-GCN: Multi-scale Multi-branch Fusion Graph Convolutional Networks for 3D Human Pose Estimation

MSMB-GCN: Multi-scale Multi-branch Fusion Graph Convolutiona...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Ji, Shanshan Meng, Qiwei Wang, Wen Lin, Zheyuan Li, Te Wan, Minhong Zhang, Chunlong Gu, Jason Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9798350325706

In human-robot interaction (HRI), human pose estimation is a necessary technology for the robot to perceive the dynamic environment and make interactive actions. Recently, graph convolutional networks (GCNs) have been increasingly used for 2D to 3D pose estimation tasks since the skeleton topologies can be viewed as graph structures. In this paper, we propose a novel graph convolutional network architecture, Multi-scale Multi-branch Fusion Graph Convolutional Networks (MSMB-GCN), for 3D Human Pose Estimation(3D HPE) task. The proposed model consists of multiple GCN blocks with a multi-branch architecture. This multi-branch architecture enables the model to get multi-scale features for human skeletal representations. The group of GCN blocks, which has strong multi-level feature extraction capabilities, allows the model to learn global and local features, lower-level and higher-level features. Experiment results on the HumanPose benchmark demonstrate that our model outperforms the state-of-the-art and ablation studies validate the effectiveness of our approach. © 2023 IEEE.

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Tracking-Differentiator-Based Sliding-Mode Control for Tracking Control

Tracking-Differentiator-Based Sliding-Mode Control for Track...

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2023 China Automation Congress, CAC 2023

作者： Li, Wenfei Li, Boyuan Hua, Wei Huang, Chao Du, Haiping Xing, Haitao Research Center for Intelligent Transportation Zhejiang Lab Hangzhou China The Hong Kong Polytechnic University Department of Industrial & Systems Engineering Hong Kong School of Electrical Computer and Telecommunications Engineering University of Wollongong Wollongong Australia

ISBN: (纸本)9798350303759

Tracking control has attracted significant attention because of its close link with industrial applications. Tracking control requires that a control algorithm can ensure that an actuator follows control commands, with a fast response anti-disturbance abilities and small chattering. A tracking-differentiator-based sliding-mode control approach for tracking control is proposed in this paper. A tracking differentiator has the ability to obtain the desired signal's differential signal, even when there is noise in the desired signal. A differential signal is often required in the design of sliding-mode controllers. When tracking differentiator is applied to a sliding-mode controller, the chattering of the control commands (caused by noise disturbance) can be reduced while the fast response of the sliding-mode controller can be maintained. The simulation results show that the proposed controller is effective. © 2023 IEEE.

关键词： Sliding mode control

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Position Control of Flexible Joint Carts Using Adaptive Generalized Dynamics Inversion

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computers, Materials & Continua 2022年第3期70卷 4691-4705页

作者： Ibrahim M.Mehedi Mohd Heidir Mohd Shah Soon Xin Ng Abdulah Jeza Aljohani Mohammed El-Hajjar Muhammad Moinuddin Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Next Generation Wireless Research Group University of SouthamptonUK

This paper presents the design and implementation of Adaptive Generalized Dynamic Inversion(AGDI)to track the position of a Linear Flexible Joint Cart(LFJC)system along with vibration suppression of the flexible *** proposed AGDI control law will be comprised of two control *** baseline(continuous)control law is based on principle of conventional GDI approach and is established by prescribing the constraint dynamics of controlled state variables that reflect the control *** control law is realized by inverting the prescribed dynamics using dynamically scaledMoore-Penrose generalized *** boost the robust attributes against system nonlinearities,parametric uncertainties and external perturbations,a discontinuous control law will be augmented which is based on the concept of sliding mode *** discontinuous control law,the sliding mode gain is made adaptive in order to achieve improved tracking performance and chattering *** closed-loop stability of resultant control law is established by introducing a positive define Lyapunov candidate function such that semi-global asymptotic attitude tracking of LFJC system is *** computer simulations followed by experimental investigation will be performed on Quanser’s LFJC system to authenticate the feasibility of proposed control approach for its application to real world problems.

关键词： Adaptive control generalized dynamic inversion moore-penrose generalized inverse sliding mode control lyapunov stability semi-global asymptotic stability

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Two-Stage Representation Refinement Based on Convex Combination for 3-D Human Poses Estimation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6500-6508页

作者： Chen, Luefeng Cao, Wei Zheng, Biao Wu, Min Pedrycz, Witold Hirota, Kaoru China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Macau University of Science and Technology Institute of Systems Engineering Taipa999078 China Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Tokyo Institute of Technology Yokohama226-8502 Japan

In the human pose estimation task, on the one hand, 3-D pose always has difficulty in dividing different 2-D poses if the view is limited;on the other hand, it is hard to reduce the lifting ambiguity because of the lack of depth information, it is an important and challenging problem. Therefore, two-stage representation refinement based on the convex combination for 3-D human pose estimation is proposed, in which the two-stage method includes a dense-spatial-temporal convolutional network and a local-to-refine network. The former is applied to determine the features between each video frame;the latter is used to get the different scales of pose details. It aims to address the difficulty of estimating 3-D human pose from 2-D image sequences. In such a way, it can better use the relations between every frame in the sequence of the pose video to produce more accurate results. Finally, we combine the above network with a block called convex combination to help refine the 3-D pose location. We test the proposed approach on both Human3.6m and MPII datasets. The result confirms that our method can achieve better performance than improved CNN supervision, a simple yet effective baseline, and coarse-to-fine volumetric prediction. Besides, a robustness test experiment is carried out for the proposed method while the input is interrupted. The result verifies that our method shows better robustness. © 2024 IEEE.

关键词： Convolution

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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case 63

Optimal Linear Deception Attacks on Remote State Estimation ...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Shang, Jun Zhang, Hanwen Zhou, Jing Chen, Tongwen Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai200092 China University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

ISBN: (纸本)9798350316339

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack's stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback-Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples. © 2024 IEEE.

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