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Dynamic Quantized control of Fuzzy Semi-Markov Jump Systems With Fading Channels: An Improved Event-Triggered Mechanism

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3519-3531页

作者： Hu, Meng-Jie Park, Ju H. Cheng, Jun Wang, Yan-Wu China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Yeungnam University Department of Electrical Engineering Gyeongsan38541 Korea Republic of Guangxi Normal University School of Mathematics and Statistics Guilin541006 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430074 China

This article focuses on the dynamic quantized control for Takagi-Sugeno fuzzy semi-Markov jump systems (T-S FSMJSs) under fading channels and deception attacks, employing an improved event-triggered mechanism (ETM) strategy. Specifically, a more generalized semi-Markov process (SMP) that is governed by a higher-level deterministic switching signal (HLDSS) is addressed. A novel dynamic ETM is skillfully developed based on the information of quantization and two internal dynamic adjusting variables to further enhance the network bandwidth utilization. The dual asynchronous phenomenon between the plant and controller (asynchronous modes and mismatched premise variables) is addressed. This implies that the designed controller is not required to share the same membership functions and modes as the plant, establishing a more rational structure. The hidden semi-Markov model (HSMM) is attained to characterize the stochastic varying channel fading amplitudes. The Lyapunov function incorporating mode and fuzzy information is constructed to establish sufficient criteria ensuring the strictly dissipative performance and mean-square exponential stability (MSES) of the resulting closed-loop systems, and a new security fuzzy dual asynchronous controller is then developed. Finally, the efficacy and applicability of the results are demonstrated through numerical and practical examples. © 2025 IEEE.

关键词： Membership functions

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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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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R-CONV: An Analytical Approach for Efficient Data Reconstruction via Convolutional Gradients 25th

R-CONV: An Analytical Approach for Efficient Data Reconstru...

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25th International Conference on Web information Systems engineering, WISE 2024

作者： Eltaras, Tamer Ahmed Malluhi, Qutaibah Savino, Alessandro Carlo, Stefano Di Qayyum, Adnan Politecnico Di Torino Control and Computer Engineering Department Turin10129 Italy Qatar University Doha Qatar Information Technology University of the Punjab Lahore Pakistan

ISBN: (纸本)9789819605750

In the effort to learn from extensive collections of distributed data, federated learning has emerged as a promising approach for preserving privacy by using a gradient-sharing mechanism instead of exchanging raw data. However, recent studies show that private training data can be leaked through many gradient attacks. While previous analytical-based attacks have successfully reconstructed input data from fully connected layers, their effectiveness diminishes when applied to convolutional layers. This paper introduces an advanced data leakage method to efficiently exploit convolutional layers’ gradients. We present a surprising finding: even with non-fully invertible activation functions, such as ReLU, we can analytically reconstruct training samples from the gradients. To the best of our knowledge, this is the first analytical approach that successfully reconstructs convolutional layer inputs directly from the gradients, bypassing the need to reconstruct layers’ outputs. Prior research has mainly concentrated on the weight constraints of convolution layers, overlooking the significance of gradient constraints. Our findings demonstrate that existing analytical methods used to estimate the risk of gradient attacks lack accuracy. In some layers, attacks can be launched with less than 5 % of the reported constraints. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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Multilayer core–shell structured FeNi_(3)@C with enhanced interfacial polarization for microwave absorbers

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Nano Research 2025年第2期18卷 833-842页

作者： Shaohan Guo Junying Zhang Chengyou Lin Jin Ge Song Bi Zhi-Ling Hou College of Mathematics and Physics Beijing University of Chemical TechnologyBeijing 100029China School of Physics and Optoelectronic Engineering Beijing University of TechnologyBeijing 100124China National Key Laboratory of Electromagnetic Information Control and Effects Shenyang Aircraft Design and Research InstituteShenyang 110035China 501 Department Xi’an Research Institute of High-TechXi’an 710025China

Magnetoelectric composites can achieve magneto-electric synergy to optimize impedance ***,it is challenging to enhance the broadband absorption performance for thin thickness ***,FeNi_(3)@C composite with magnetic alloy core and N-doped macroporous multilevel layered carbon shell was constructed by hierarchical interface *** uniform multilevel layered carbon shell could induce interfacial polarization and multiple scattering,and further endows enhanced electromagnetic attenuation and optimized impedance *** ultra-thin broadband absorber with an effective absorption bandwidth of 7.4 GHz is achieved at a thickness of only 1.6 ***,full-band absorption from 2 to 18 GHz at a thickness of 9.8 mm is realized through metastructure *** work provides an alternative strategy to prepare coreshell structured magnetoelectric composites for ultra-thin and broadband absorbers.

关键词： covalent organic frameworks(COFs) FeNi_(3)@C core-shell structure interfacial polarization impedance matching

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The Internet of Things under Federated Learning:A Review of the Latest Advances and Applications

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Computers, Materials & Continua 2025年第1期82卷 1-39页

作者： Jinlong Wang Zhenyu Liu Xingtao Yang Min Li Zhihan Lyu School of Information and Control Engineering Qingdao University of TechnologyQingdao260043China Anhui Province Key Laboratory of Intelligent Building&Building Energy Saving Anhui Jianzhu UniversityHefei230000China Department of Game Design Uppsala UniversityUppsala75310Sweden

With the rapid development of artificial intelligence,the Internet of Things(IoT)can deploy various machine learning algorithms for network and application *** the IoT environment,many sensors and devices generatemassive data,but data security and privacy protection have become a serious *** learning(FL)can achieve many intelligent IoT applications by training models on local devices and allowing AI training on distributed IoT devices without data *** review aims to deeply explore the combination of FL and the IoT,and analyze the application of federated learning in the IoT from the aspects of security and privacy *** this paper,we first describe the potential advantages of FL and the challenges faced by current IoT systems in the fields of network burden and privacy ***,we focus on exploring and analyzing the advantages of the combination of FL on the Internet,including privacy security,attack detection,efficient communication of the IoT,and enhanced learning *** also list various application scenarios of FL on the ***,we propose several open research challenges and possible solutions.

关键词： Federated learning Internet of Things sensors machine learning privacy security

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Broadband Optical Nonlinearities and Ultrafast Carrier Dynamics of GO-CuS Hybrid Film

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Journal of Lightwave technology 2025年第11期43卷 5381-5389页

作者： Zhang, Xuefeng Bai, Xuli Liu, Xiaofei Wang, Dan Han, Hong Xiao, Zhengguo Zhang, Jianguo Nie, Zhongquan Taiyuan University of Technology College of Materials Science and Engineering Institute of New Carbon Materials Taiyuan030024 China Taiyuan University of Technology Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Electronic Information and Optical Engineering Taiyuan030024 China Taiyuan Institute of Technology Department of Science Taiyuan030008 China Tongren University Department of Physics and Electronic Engineering Tongren China National University of Defense Technology College of Advanced Interdisciplinary Studies Changsha410073 China

We report the broadband optical nonlinearities and ultrafast carrier dynamics of GO doped with CuS nanoparticles (GO-CuS) following the femtosecond pulse lasers. Both the pure GO and GO-CuS hybrid films are first synthesized by the vacuum filter deposition method and their optical nonlinearities are then examined in the wide wavelength range (400 nm-1064 nm) based on the femtosecond Z-scan technique. The results reveal that, compared to the pristine GO, the introduction of CuS not only makes the GO-CuS hybrid film switched from saturated absorption to reverse saturated absorption possible, but also achieves strong broadband optical nonlinear absorption responses and optical limiting effects. It is demonstrated that the strongest nonlinear absorption coefficient (∼3.6×10-7 m/W) appears at 400 nm excitation, which is dozens of times larger than that under the illumination of 1064 nm. By leveraging the femtosecond pump-probe technique, we further study the ultrafast carrier dynamics of the GO-CuS hybrid film carrying the fast and slow relaxation processes. Moreover, the physical mechanisms behind these excellent nonlinear optical responses are elucidated. The findings presented here indicate that the GO-CuS hybrid film can be regarded as a potential promising candidate in various ultrafast photonics devices. © 1983-2012 IEEE.

关键词： Femtosecond lasers

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Designing Quantum-Resilient Blockchain Frameworks: Enhancing Transactional Security with Quantum Algorithms in Decentralized Ledgers

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International Journal of Advanced Computer Science and Applications 2025年第4期16卷 618-628页

作者： Kale, Meenal R. Baker El-Ebiary, Yousef A. Sathiya, L. Burugari, Vijay Kumar Yulduz, Erkiniy Muniyandy, Elangovan Alanazi, Rakan Department of Humanities Yeshwantrao Chavan College of Engineering Hingna Nagpur India Faculty of Informatics and Computing UniSZA University Malaysia Department of CSE Panimalar Engineering College Chennai India Dept of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India Automatic Control and Computer Engineering Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan Department of Biosciences-Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Applied Science Research Center Applied Science Private University Amman Jordan Department of Information Technology Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia

Quantum computing is progressing at a fast rate and there is a real threat that classical cryptographic methods can be compromised and therefore impact the security of blockchain networks. All of the ways used to secure blockchain like Rivest–Shamir–Adleman (RSA), Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm 256-bit (SHA256) are the characteristic of the traditional cryptographic techniques vulnerable to attack by quantum algorithms: Shor’s and Grover’s algorithms: can efficiently break asymmetric encryption and speed up brute force attacks. Because of this vulnerability, there exists a need to develop an advance quantum resilient blockchain framework to protect the decentralized ledgers from the future threats of the quantum. This research proposes Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD) and Quantum Random Number Generation (QRNG) as a formidable architectural integration, to fortify security of blockchain. Classical encryption is replaced with PQC, QKD with secure key exchange by detecting eavesdropping, and QRNG with improving cryptographic randomness to remove the predictable key vulnerability. Only with a small loss of transaction efficiency, we increase transaction encryption accuracy, key exchange security, and resistance to quantum attacks. In this quantum enhanced blockchain design, the idea is to preserve the decentralization, transparency and security and at the same time overcome the future quantum threat. By going through rigorous analysis and comparative evaluation, we demonstrate that the approach saves blockchain networks from the emerging quantum risks to make sure that the decentralized finance, smart contracts and cross chain transactions. © (2025), (Science and information Organization). All rights reserved.

关键词： Quantum cryptography

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Underwater arbitrary ranging based on chirped pulse interferometry with a mode-locked laser

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Journal of Lightwave technology 2025年第11期43卷 5235-5243页

作者： Shi, Haonan Zhao, Haihan Xu, Xinyang Zhu, Zhiwei Zhai, Jingsheng Li, Xiaobo Tianjin University School of Marine Science and Technology Tianjin300072 China Research Institute of China Electronics Technology Group Corporation Science and Technology on Electro-Optical Information Security Control Laboratory No. 53 Tianjin300308 China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Hong Kong999077 Hong Kong Nanjing University of Aeronautics and Astronautics Key Laboratory of Space Photoelectric Detection and Perception Ministry of Industry and Information Technology Nanjing211106 China

Underwater distance measurement and length sensing, as fundamental functions of geoscience, are integrated into underwater robots and vessels in various forms of sensor payloads and play a crucial role in a wide range of remote sensing applications. Advanced laser-based detection systems and algorithms are essential for underwater tasks, such as detecting damage in underwater pipelines and conducting detailed structural health assessments. In this paper, we experimentally demonstrated an arbitrary underwater ranging system by the chirped pulse interferometry with a mode-locked laser. Water's inherent characteristic introduces dispersion, enabling unique distance discrimination. Adjusting the repetition frequency allows us to acquire the interference spectrum. A long fiber delay line, stabilized by the servo-controlled system, eliminates the ranging dead zone. The widest fringe of the interference spectrum, corresponding to an instantaneous repetition frequency, indicates the arbitrary measured distance. Leveraging a charge-coupled device detection module, we achieved an update rate of 13.5 Hz for the interference spectrum. Experimental results show a precise distance difference within 59.8 μm at the 5 m range underwater without the dead zone. © 2025 IEEE. All rights reserved.

关键词： Laser mode locking

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Topology-Driven Attribute Recovery for Attribute Missing Graph Learning in Social Internet of Things

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IEEE Internet of Things Journal 2025年第11期12卷 16298-16313页

作者： Li, Mengran Chen, Junzhou Yu, Chenyun Jiang, Guanying Zhang, Ronghui Shen, Yanming Song, Houbing Herbert Shenzhen Campus of Sun Yat-sen University School of Intelligent Systems Engineering Shenzhen518107 China Baidu Inc Beijing100085 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education School of Electronic Information and Electrical Engineering Dalian116024 China Department of Information Systems Baltimore County BaltimoreMD21250 United States

With the advancement of information technology, the Social Internet of Things (SIoT) has fostered the integration of physical devices and social networks, deepening the study of complex interaction patterns. Text Attribute Graphs (TAGs) capture both topological structures and semantic attributes, enhancing the analysis of complex interactions within the SIoT. However, existing graph learning methods are typically designed for complete attributed graphs, and the common issue of missing attributes in Attribute Missing Graphs (AMGs) increases the difficulty of analysis tasks. To address this, we propose the Topology-Driven Attribute Recovery (TDAR) framework, which leverages topological data for AMG learning. TDAR introduces an improved pre-filling method for initial attribute recovery using native graph topology. Additionally, it dynamically adjusts propagation weights and incorporates homogeneity strategies within the embedding space to suit AMGs' unique topological structures, effectively reducing noise during information propagation. Extensive experiments on public datasets demonstrate that TDAR significantly outperforms state-of-the-art methods in attribute reconstruction and downstream tasks, offering a robust solution to the challenges posed by AMGs. The code is available at https://***/limengran98/TDAR. © 2014 IEEE.

关键词： Undirected graphs

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