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A time-varying image encryption algorithm driven by neural network

OPTICS AND LASER TECHNOLOGY 2025年 186卷

作者： Zhang, Hangming Hu, Hanping Ding, Weiping Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Minist Educ Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Peoples R China Nantong Univ Sch Artificial Intelligence & Comp Sci Nantong 226019 Peoples R China

Nowadays, the application of neural networks, genetic operations, and chaos to image encryption algorithms has become a focused area of frontier research. The neuronal mechanism and deep neural network have good nonlinear characteristics and meet the anti-aggression demands for cryptosystem security. What cannot be ignored is that due to multiplications between matrices in the computation of neuronal mechanisms and deep neural networks, the activation function cannot precisely recover the image, and the direct application of image encryption by neurons and deep neural networks cannot obtain secure results. Moreover, the performance of the adopted chaotic systems also determines the safety level of the cryptosystem. The fixed coupling structures in current research make the dynamic behavior easy to predict, bringing vulnerability to cryptosystems. Considering the aforesaid flaws, an image encryption algorithm using the neural-network pattern, genetic algorithm, and time-varying coupling structure of the chaotic system is proposed, helping improve the security and efficiency of our cryptosystem. Firstly, a time-varying coupled chaotic system is proposed, and highly stochastic sequences are used as keystreams. Then, the keystreams are processed using the neural-network mode and genetic operation to complete scrambling and diffusing. Ultimately, the simulations and security analyses indicate that our method reaches a highly safe level, which shows high efficiency and strong security, and meets the demands of various security applications.

关键词： Neural network Nerve cell Genetic operation Convolution lattice Chaos image encryption

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Learning Probabilistic Coordinate Fields for Robust Correspondences

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2023年第10期45卷 12004-12021页

作者： Zhao, Weiyue Lu, Hao Ye, Xinyi Cao, Zhiguo Li, Xin Huazhong University of Science and Technology The Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Wuhan430074 China West Virginia University The Lane Department of Computer Science and Electrical Engineering MorgantownWV26506-6109 United States

We introduce Probabilistic Coordinate Fields (PCFs), a novel geometric-invariant coordinate representation for image correspondence problems. In contrast to standard Cartesian coordinates, PCFs encode coordinates in correspondence-specific barycentric coordinate systems (BCS) with affine invariance. To know when and where to trust the encoded coordinates, we implement PCFs in a probabilistic network termed PCF-Net, which parameterizes the distribution of coordinate fields as Gaussian mixture models. By jointly optimizing coordinate fields and their confidence conditioned on dense flows, PCF-Net can work with various feature descriptors when quantifying the reliability of PCFs by confidence maps. An interesting observation of this work is that the learned confidence map converges to geometrically coherent and semantically consistent regions, which facilitates robust coordinate representation. By delivering the confident coordinates to keypoint/feature descriptors, we show that PCF-Net can be used as a plug-in to existing correspondence-dependent approaches. Extensive experiments on both indoor and outdoor datasets suggest that accurate geometric invariant coordinates help to achieve the state of the art in several correspondence problems, such as sparse feature matching, dense image registration, camera pose estimation, and consistency filtering. Further, the interpretable confidence map predicted by PCF-Net can also be leveraged to other novel applications from texture transfer to multi-homography classification. © 1979-2012 IEEE.

关键词： image registration

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Global Exponential Stabilization of Delayed T-S Fuzzy Systems on Time Scales Under DoS Attacks

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2024年第5期32卷 3237-3246页

作者： Sheng, Yin Liu, Kexin Xiao, Qiang Huang, Tingwen Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Texas A&M Univ Qatar Sci Program Doha 23874 Qatar

In this article, global exponential stabilization of Takagi-Sugeno (T-S) fuzzy systems with discrete time-varying delays on time scales under denial-of-service (DoS) attacks is investigated. When a DoS attack occurs, the control channel is blocked and the controller is disabled. Combining analytical method, inequality techniques, and time scale theory, stabilization criterion for the underlying systems is obtained via a fuzzy controller. Furthermore, the corresponding outcomes on continuous and discrete time domains are provided, respectively. Finally, two numerical simulations and an application of the Chua's circuit are exhibited to validate the effectiveness of the theories.

关键词： Discrete time-varying delays DoS attacks exponential stabilization Takagi-Sugeno (T-S) fuzzy systems time scale

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Disturbance Rejection control for Networked control Systems Using Subpredictor-Based Extended State Observer

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2023年第6期53卷 3629-3639页

作者： Sun, Jiankun Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Peoples R China

In this article, we consider the disturbance rejection control problem for networked control systems using a subpredictor-based extended state observer. The networked control system is subject to large input and output delays. To handle the time delays, a subpredictor-based extended state observer is proposed to estimate the unknown state and disturbance by dividing the total delay into small pieces. The proposed observer is composed of a set of predictor-based observers connected in series, and each elementary observer is only responsible for compensating the effect of a fraction of the total delay. By using the disturbance compensation technique, we design a sampled-data composite controller to attenuate the influence of external disturbance. The proposed control method can handle the multirate case where the sensor and controller have different sampling and updating rates. It shows that under the proposed control method, the disturbance rejection ability of the control system can be effectively improved in the presence of arbitrary large input and output delays. The simulation results are given to demonstrate the effectiveness of the proposed control method.

关键词： Delays Observers Networked control systems Delay effects Robust control Feedback control Estimation External disturbance input and output delays multirate control networked control system subpredictor-based extended state observer

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WDNet: A Water Depth Perception Network with Global Information 42

WDNet: A Water Depth Perception Network with Global Informat...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Zhihui Tang, Yifeng Tang, Chuancong Xu, Yifan Luo, Chuanshang Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

Deep perception of the unmanned surface vehicle's surroundings is an inaccessible part of its fully autonomous navigation mission. The existing methods, whether based on traditional stereo matching or deep learning, do not fully consider the characteristics of water environment, resulting in severe error depths in weak textures (sky, calm lake) and water reflections regions, that increases the risk of running aground or collision. What is worse that there is not a public dataset for depth estimation in the water environment. Therefore, this work proposes a self-supervised model for depth estimation named Water Depth Perception Network (WDNet) to address these problems. The decoder of this network has a wider receptive field and can effectively handle the depth error in the weak texture region. Besides, the WDNet is trained with a novel and effective loss function which assist the network to reduce errors in sky and water region, and some indexes are proposed to evaluate the model's performances in sky and water region. Finally, our proposed WDNet achieves a 0.1056 absolute relative error in ranging, the average number of error pixels in the sky area drops from 15803.87 to 580.91, which only accounted for 0.29% of the image, and the error in water region drops from 51.04 to 6.75, all of them are superior to the performance of baseline model. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Errors

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Game-based Secondary control for DC Microgrids with Nash Equilibrium

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IEEE Transactions on Energy Conversion 2025年

作者： Yuan, Qi-Fan Wang, Yan-Wu Liu, Xiao-Kang Guo, Kai-Yuan Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China

Voltage regulation and current sharing are two major issues when designing distributed control strategies for DC microgrids. However, power supply economy of local generators also needs to be considered. In this paper, a game-based framework is constructed, where multiple generators are regarded as the participants with secondary control signals being the game actions. A distributed secondary control algorithm is proposed, while information mask is introduced to avoid transmitting true control signal to neighbors. Then, payoff function is designed for each generator, which is composed of voltage regulation error, current sharing error and the local generation cost. It is proved that under the proposed secondary control algorithm in conjunction with the payoff function, a unique Nash equilibrium can be reached. Consequently, the minimum of the payoff function can be achieved, where the optimization of system control behavior and local economic operation can be realized simultaneously. Numerical simulations and experimental tests are carried out to demonstrate the effectiveness of the proposed secondary control strategy within several scenarios. © 1986-2012 IEEE.

关键词： Microgrids

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Composite Finite-Time Resilient control for Cyber-Physical Systems Subject to Actuator Attacks

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IEEE TRANSACTIONS ON CYBERNETICS 2023年第2期53卷 1063-1077页

作者： Zhao, Yue Zhou, Chunjie Tian, Yu-Chu Qin, Yuanqing Huazhong Univ Sci & Technol Key Lab Sch Artificial Intelligence & Automat Minist Educ Image Proc & Intelligent Control Wuhan 430074 Peoples R China Queensland Univ Technol Sch Comp Sci Brisbane Qld 4001 Australia

Cyber-physical systems (CPSs) seamlessly integrate communication, computing, and control, thus exhibiting tight coupling of their cyber space with the physical world and human intervention. Forming the basis of future smart services, they play an important role in the era of Industry 4.0. However, CPSs also suffer from increasing cyber attacks due to their connections to the Internet. This article investigates resilient control for a class of CPSs subject to actuator attacks, which intentionally manipulate control commands from controllers to actuators. In our study, the supertwisting sliding-mode algorithm is adopted to construct a finite-time converging extended state observer (ESO) for estimating the state and uncertainty of the system in the presence of actuator attacks. Then, for the attacked system, a finite-time converging resilient controller is designed based on the proposed ESO. It integrates global fast terminal sliding-mode and prescribed performance control. Finally, an industrial CPS, permanent magnet synchronous motor control system, is investigated to demonstrate the effectiveness of the composite resilient control strategy presented in this article.

关键词： Actuators Uncertainty control systems Asymptotic stability Cyberattack Convergence Observers Actuator attacks cyber-physical systems (CPSs) extended state observer (ESO) finite-time converging global fast terminal sliding-mode control prescribed performance control resilient control

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Dynamic Graph Dismantling with Reinforcement Supervised Learning 42

Dynamic Graph Dismantling with Reinforcement Supervised Lear...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Yumei Tang, Chuancong Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

There are always some 'key' nodes in a big complex network, which can joint the most connected subgraphs. How to identify these nodes, finding a minimum set of nodes to attack for reducing the size of residual network's Largest Connected Component(LCC) to break up the original network, has become a research hotspot. Therefore, a method for determining the 'key' nodes based on reinforcement learning framework and supervised learning model is proposed. This algorithm can not only utilize the dynamic exploration ability of reinforcement learning to collect a rich training dataset, but also take advantage of the characteristics that supervised learning is adaptive and has strong generalization ability to possess high efficiency and strong robustness. In order to further improve the algorithm's performance, ϵ-greedy mechanism is used to explore more network states. The experiment results show that given the same fraction of removed nodes, our algorithm can make the residual LCC smaller in various networks which is superior to the state-of-the-art algorithms in terms of effectiveness and generalization. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Complex networks

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Uniform Solution to QSAT by P Systems with Proteins

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Chinese Journal of Electronics 2023年第4期21卷 667-672页

作者： Chun LU Xiaolong SHI Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

P systems are distributed parallel computing models in the area of membrane computing, which are inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order structures. P systems with proteins on membranes are a class of P systems, which have proved to be very efficient computing devices. Specifically, it was known that the Quantified satisfiability problem (QSAT) of a Boolean formula can be solved by a semi-uniform family of P systems with proteins on membranes and with membrane division. However, it remains open whether a uniform families of P systems with proteins on membranes can solve in polynomial time exactly the class of problems PSPACE. In this work, we present a uniform solution to QSAT problem by P systems with proteins on membranes in a linear time with respect to both the number $n$ of Boolean variables and the number $m$ of clauses of the instance, which answers the above open problem.

关键词： Proteins image processing Computational modeling Organizations Parallel processing intelligent control

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Spiking Neural P Systems With Communication on Request and Mute Rules

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2023年第2期34卷 734-745页

作者： Wu, Tingfang Pan, Linqiang Soochow Univ Sch Comp Sci & Technol Prov Key Lab Comp Informat Proc Technol Suzhou 215006 Peoples R China Huazhong Univ Sci & Technol Inst Artificial Intelligence Sch Artificial Intelligence & Automat Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Peoples R China

Spiking neural P systems with communication on request (SNQP systems) are neurally inspired computing devices, where a neuron actively seeks spikes from presynaptic neurons instead of passively waiting for spikes. In this work, we consider SNQP systems with mute rules (SNQPM systems), where mute rules have no communication functioning, namely the application of a mute rule only affects the number of spikes in the neuron where the rule resides, without effect on other neurons. It is demonstrated the computation capability of SNQPM systems with only mute rules does not exceed that of register machines with two registers, thereby not Turing universal. SNQPM systems are Turing universal when both mute rules and request rules are employed. Furthermore, two universal SNQPM systems with 7 neurons or 13 neurons are constructed as devices of number generating and function computing, respectively. Comparing to the universal SNQP system with 14 neurons and two types of spikes, SNQPM systems show the capability of trading-off mute rules and the types of spikes.

关键词： Bio-inspired computing distributed architectures neural computation spiking neural P system computation capability

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