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Adversarial attacks and defenses in physiological computing:a systematic review

National science Open 2023年第1期2卷 62-90页

作者： Dongrui Wu Jiaxin Xu Weili Fang Yi Zhang Liuqing Yang Xiaodong Xu Hanbin Luo Xiang Yu Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Zhejiang Lab Hangzhou 311121China School of Civil and Hydraulic Engineering Huazhong University of Science and TechnologyWuhan 430074China College of Public Administration Huazhong University of Science and TechnologyWuhan 430074China Electrical Engineering and Computer Science Department University of MichiganAnn Arbor MI 48109USA School of Management and Sino-European Institute for Intellectual Property Huazhong University of Science and TechnologyWuhan 430074China

Physiological computing uses human physiological data as system inputs in real *** includes,or significantly overlaps with,brain-computer interfaces,affective computing,adaptive automation,health informatics,and physiological signal based *** computing increases the communication bandwidth from the user to the computer,but is also subject to various types of adversarial attacks,in which the attacker deliberately manipulates the training and/or test examples to hijack the machine learning algorithm output,leading to possible user confusion,frustration,injury,or even ***,the vulnerability of physiological computing systems has not been paid enough attention to,and there does not exist a comprehensive review on adversarial attacks to *** study fills this gap,by providing a systematic review on the main research areas of physiological computing,different types of adversarial attacks and their applications to physiological computing,and the corresponding defense *** hope this review will attract more research interests on the vulnerability of physiological computing systems,and more importantly,defense strategies to make them more secure.

关键词： physiological computing brain-computer interfaces health informatics biometrics machine learning adversarial attack

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Liquid Metal Enabled Conductive Zwitterionic Hydrogel for Robust Electrochemical Sensing in Complex Serum

SSRN

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SSRN 2024年

作者： Ma, Jiao Li, Shikang Li, Xiaoting Wang, Hua Key Laboratory of Interface Science and Engineering in Advanced Materials Ministry of Education Taiyuan University of Technology Shanxi Taiyuan030024 China North Automatic Control Technology Institute Shanxi Taiyuan030006 China

Any materials present in complex samples that bind the sensing interface non-specifically will greatly decrease the sensitivity and accuracy of the electrochemical sensor. Zwitterionic hydrogel have exhibited extraordinary antifouling ability, but they are limited by the electrical insulativity and weak interface, resulting in a double-edged strategy. Herein, we proposed a novel approach to resolve this challenge thanks to the liquid metal (LM). It was found that with only ultrasonic treatment, a core-shell nanostructure could be easily formed between LM matrix and sodium alginate (SA) polymer, accompanied with the generation of lots of free radical, which initiated the polymerization of zwitterionic monomer and further crosslinking with methylacrylated bovine serum albumin. The whole process involved no synthesis of conductive nanomaterials or addition of initiators. More remarkably, the acquired superhydrophilic hydrogel exhibited a surprisingly favourable adhesion to the electrode surface, attributed to the carboxyl groups and related denser gel network resulting from the LM@SA nanoparticles. Finally, the prepared electrochemical immunosensor possessed excellent repeatability, storage stability, selectivity and meanwhile a wide linear range from 10 pg mL-1 - 100 ng mL-1, and an ultralow detection limit of 8.23 pg mL-1 for the detection of motilin even in 100% human serum. Moreover, this is a successful attempt of LM-based nanocomposite hydrogel as an electrochemical sensing matrix, and we believe it could present further opportunities toward more satisfying sensing interface for biosensing and bioelectronics with more research in future. © 2024, The Authors. All rights reserved.

关键词： Hydrogels

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Deformation Pattern Shape Sensing for Visuotactile Endoscope

Deformation Pattern Shape Sensing for Visuotactile Endoscope

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Yu, Yanzhe Tian, Yuan Cui, Shaowei Wang, Yupeng Wang, Rui Wang, Shuo Beijing University of Science and Technology Beijing100083 China The University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9798350372601

The integration of visuotactile sensor technology with endoscopy enables the provision of tactile information for minimally invasive surgeries and other operations. This paper proposes a real-time sensing framework for contact deformation pattern shape, providing a foundation for precise perception in miniaturized visuotactile sensors. Specifically, we first construct a Deformation Pattern shape Descriptor (DPSD) and then track the key points in the descriptor using optical flow to obtain contact deformation shape information. Through extensive qualitative and quantitative experiments, our proposed algorithm achieves an average perception accuracy of around 83.81% for contact pattern shapes. It demonstrates consistent perception accuracy across various contact force magnitudes, directions, and scenarios, highlighting its robustness. Additionally, compared to traditional marker-level methods, it achieves a notable 46.5% improvement in displacement field perception accuracy. This research elevates tactile perception to the dimension of contact pattern shape sensing and has the potential for application in miniaturized visual tactile sensors. © 2024 IEEE.

关键词： Endoscopy

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Resilient Cooperative control of Multiple DC Microgrids With Interconnection Networks Against Cyber Attacks

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 116-126页

作者： Xiao, Feng Liu, Shiyu Wei, Bo Fang, Fang Qin, Jiahu North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China North China Electric Power University School of Control and Computer Engineering Beijing102206 China North China Electric Power University New Energy Generation National Engineering Research Center Beijing102206 China University of Science and Technology of China Department of Automation Hefei230027 China

The two control objectives of voltage regulation and precise current sharing are conflicting in multi-bus DC microgrids. In this paper, a distributed control strategy is proposed, and it can achieve accurate current sharing and regulate the voltage of a critical node to the rated value. However, such a distributed control system is susceptible to potential cyber attacks that could deteriorate microgrids performances by corrupting communication links or actuators. To overcome these difficulties, we design the interconnected communication networks to establish a resilient cooperative system of multiple microgrids against unknown bounded injection attacks. The proposed resilient control strategy can achieve the control objectives of maintaining voltage regulation and current sharing within each microgrids under different operating conditions, and the interconnected system consisting of multiple microgrids cooperates to mitigate the adverse effect of cyber attacks. The dynamics and stability of the overall close-loop system of the DC microgrids are analyzed, in the present or absent of cyber attacks. Simulation results validate the effectiveness of the proposed approach in two 4-bus DC microgrids. © 2023 IEEE.

关键词： Cyber attacks

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Roblets: Robotic Tablets That Self-Assemble and Self-Fold into a Robot

Roblets: Robotic Tablets That Self-Assemble and Self-Fold in...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Junyi Han Daniela Rus Shuhei Miyashita Automatic Control and Systems Engineering Department University of Sheffield Sheffield UK Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA Insigneo Institute for in silico Medicine

Inspired by human proteins that are synthesized from only 20 types of amino acids, the development of self-assembly methods that allow robots to be built simply by randomly stirring the parts has been explored for many years. The key challenges include how to synthesize parts in pieces into a three-dimensional functional structure in a practical time, and subsequently, achieve a controlled robotic motion, all with minimal human intervention. This study proposes a method of self-assembling a 3D robot by first self-assembling random parts into a 2D structure and then self-folding it into a 3D shape. Once self-folded, the robot, whose compositional parts contain magnets, becomes capable of performing basic tasks such as block-pushing upon an application of an external magnetic field. Self-assembly from parts into a two-dimensional structure was performed by repeatedly colliding the parts with each other, and combining them with complementary-shaped parts, like matching jigsaw puzzle pieces. Self-folding was performed by shrinking a heat-responsive film attached across the hinge of each assembly part in hot water, causing the entire 2D structure to self-fold. The experiment demonstrated a series of 13 parts self-assembling into the shape of a 3D beetle, then walking and pushing an object in 13 minutes. The self-assembly process is programmed (mechanically) to generate the same geometry even if the number of parts is greater than the necessary number for the structure, thus is capable of generating multiple structures simultaneously.

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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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Multi-Modal Domain Adaptation Variational Autoencoder for EEG-Based Emotion Recognition

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IEEE/CAA Journal of automatica Sinica 2022年第9期9卷 1612-1626页

作者： Yixin Wang Shuang Qiu Dan Li Changde Du Bao-Liang Lu Huiguang He the Research Center for Brain-inspired Intelligence National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of ScienceBeijing 100190 the University of Chinese Academy of Sciences Beijing 100049 the Beijing Institute of Control and Electronic Technology Beijing 100038China the School of Mathematics and Information Sciences Yantai UniversityYantai 264003China the Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of ScienceBeijingChina the Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Traditional electroencephalograph(EEG)-based emotion recognition requires a large number of calibration samples to build a model for a specific subject,which restricts the application of the affective brain computer interface(BCI)in *** attempt to use the multi-modal data from the past session to realize emotion recognition in the case of a small amount of calibration *** solve this problem,we propose a multimodal domain adaptive variational autoencoder(MMDA-VAE)method,which learns shared cross-domain latent representations of the multi-modal *** method builds a multi-modal variational autoencoder(MVAE)to project the data of multiple modalities into a common *** adversarial learning and cycle-consistency regularization,our method can reduce the distribution difference of each domain on the shared latent representation layer and realize the transfer of *** experiments are conducted on two public datasets,SEED and SEED-IV,and the results show the superiority of our proposed *** work can effectively improve the performance of emotion recognition with a small amount of labelled multi-modal data.

关键词： Cycle-consistency domain adaptation electroencephalograph(EEG) multi modality variational autoencoder

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Dynamic Adjustment of Packet Based on Fair Bandwidth Allocation in IEEE 802.11 Wireless Networks 12

Dynamic Adjustment of Packet Based on Fair Bandwidth Allocat...

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12th International Conference on Information technology in Medicine and Education, ITME 2022

作者： Zou, Xiong Gao, Jinfeng Zhang, Yu Li, Huyong Liu, Fang Wu, Haitao Lu, Shejie Hu, Siping Huanghuai University College of Computer and Artificial Intelligence International Joint Laboratory of Behavior Optimization Control for Smart Robots Zhumadian China Hubei University of Science and Technology Institute of Engineering and Technology Xianning China

ISBN: (纸本)9798350310153

In view of the imbalance of upstream and downstream flows in the access of local manufacturing resources, this paper proposes a dynamic adjustment algorithm based on bandwidth fair allocation (DAPFBA, Dynamic Adjustment of Packet based on Fair Bandwidth Allocation), which dynamically adjusts the packet size of nodes according to the number of downflows and realizes the downstream throughput balance, so as to realize the fair distribution of upstream and downstream bandwidth. According to the actual situation of the network, the algorithm can be implemented in the AP without modifying the MAC of other wireless nodes, which saves the workload of the implementation. Especially in the case of more and scattered wireless nodes, it only needs to modify the AP without modifying other nodes, eliminating a lot of work to configure the decentralized nodes. © 2022 IEEE.

关键词： Bandwidth

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Sea ice type identification method based on MEMS sensor network combined with PCA-BPMIV-GRU

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： Yang, Le Quan, Xiyu Zhang, Jiankui Liu, Yunjing Zhao, Shiqi Fu, Changzeng Zhan, Zhikun Li, Lianliang Lv, Xiaoyong Zhao, Yuliang Northeastern University at Qinhuangdao Hebei Key Laboratory of MicroNano Precision Optical Sensing and Measurement Technology The School of Control Engineering Qinhuangdao066004 China Northeastern University at Qinhuangdao College of Control Science and Engineering Qinhuangdao066099 China Northeastern University at Qinhuangdao College of Computer Science and Engineering Qinhuangdao066004 China

Sea ice poses a significant hazard to vessels navigating in high-latitude maritime regions. To effectively prevent the collision between ships and large sea ice (such as icebergs) and other similar accidents, it is crucial to identify sea ice and its types in a timely and accurate manner. However, traditional sea ice identification techniques, such as optical and radar remote sensing, are often limited by visibility conditions, suffering from poor accuracy, high measurement costs, and low identification efficiency. This paper proposes a sea ice identification method based on a vibration sensor network, combined with the PCA-BPMIV-GRU strategy, which achieves low cost, high efficiency, and high accuracy in sea ice type detection. Firstly, a cost-effective MEMS vibration sensor network is deployed to capture vibration information of sea ice. The data collected from six sensors at different locations at the same time are treated as independent samples to construct a dataset, which contains time-frequency domain characteristic data of three sea-ice types: broken ice, flat ice, and open water. Secondly, the dimension reduction and feature optimization of vibration data were carried out by combining Principal Component Analysis (PCA) and the improved Mean Influence Value Optimization algorithm (BPMIV). This integration of unsupervised and supervised algorithms effectively eliminated unnecessary feature information, significantly improving model identification efficiency. Finally, seven commonly used classification algorithms are compared for the identification of three types of sea ice, evaluating their identification accuracy and efficiency under different dimensionality reduction methods. The results confirm that the Gated Recurrent Unit (GRU) model achieves the best comprehensive performance. Experimental data shows that the proposed method reduces the number of features to 9, resulting in a 24.2 % decrease in parameters compared to the GRU model alone, while achieving

关键词： Frequency domain analysis

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Exploration of the application of optimisation algorithm using stochastic gradient descent method in satellite resource allocation

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Applied Mathematics and Nonlinear sciences 2024年第1期9卷

作者： Zhao, Demin Xiong, Wei Shi, Jinjing Science and Technology on Complex Electronic System Simulation Laboratory University of Aerospace Engineering Beijing101400 China Dfh Satellite CO. Ltd Beijing100080 China North Automatic Control Technology Institute Shanxi Taiyuan030006 China

With the popularization and development of communication technology, the resource allocation problem of satellites has become a hot research topic. This study proposes a model for satellite resource allocation through the development of a beam mobilization system model and problem modeling. Then, on the basis of the linear stochastic gradient descent method, the classification accuracy of the algorithm is improved by adjusting the algorithm-solving method. Then its weight assignment method is improved to get the improved weighted linear stochastic gradient descent method. Using the optimized weighted linear stochastic gradient descent method to solve the satellite resource allocation problem from the perspective of the original problem, a model based on IWLSGD is designed and tested for performance. Through simulation experiments, the beam allocation service value of the satellite resource allocation model in this paper is 193, which is 4.32% and 3.21% higher than that of LSGD and WLSGD, respectively, and iterative convergence is faster, and its operation time and service value performs the best under different numbers of communication time slots. The system revenue, system access success rate, and system satisfaction under the interference environment between LEO and GEO are maintained at 15208, 0.8~1.0, and 85%, and keep around 7500, 1, and 75% under 5G base station interference. The satellite resource allocation model in this paper can effectively improve the utilization efficiency of communication resources and better adapt to dynamically changing interference scenarios. © 2024 Demin Zhao et al., published by Sciendo.

关键词： Resource allocation

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