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23rd International Conference on control Systems and computer science Technologies, CSCS 2021

作者： Apostol, Teodor-Petrut Velea, Radu Deaconescu, Razvan University Politehnica of Bucharest Faculty of Automatic Control and Computers Computer Science and Engineering Department Romania

ISBN: (纸本)9781665439398

Graphics processing units (GPU) are an integral part of today's computing environment. The marketing emphasis on user experience pushes vendors to constantly look for better graphics hardware and newer drivers to integrate into their products. Most commodity GPUs function as accelerators for image and video processing tasks and are present (either as dedicated or integrated form factor) in everyday devices including desktops, laptops, smartphones or other portable gadgets. Recent trends have seen the GPU move to perform additional tasks such as offloading some of the computation from the CPU or solve highly parallel problems. As GPUs become more powerful and widespread they will naturally become a very attractive target for attackers. Cybercriminals will look for any vulnerability in the GPU hardware or software, and will try to use it as an attack vector to compromise the system. This paper presents some of the incidents that involve the use of GPUs to perform malicious actions and proposes a framework to allow analysts to inspect the code executed on the GPU and trigger security alerts. The proposed solution will look at the processes running inside an operating system, it will identify which of them require access to the GPU and will try to intercept and scan for any suspicious activities, similar to a conventional security solution. © 2021 IEEE.

关键词： Graphics processing unit

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A Coding-Enhanced Jamming Approach for Secure Semantic Communication over Wiretap Channels

arXiv

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arXiv 2025年

作者： Chen, Weixuan Q., Yang S., Shao Z., Shi J., Chen X., Shen College of Information Science and Electronic Engineering Zhejiang University Hangzhou China School of Cyber Science and Engineering Shanghai Jiao Tong University Shanghai China College of Control Science and Engineering Zhejiang University Hangzhou China Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada

As semantic communication (SemCom) gains increasing attention as a novel communication paradigm, ensuring the security of transmitted semantic information over open wireless channels becomes crucial. Existing secure SemCom solutions often lack explicit control over security. To address this, we propose a coding-enhanced jamming approach for secure SemCom over wiretap channels. This approach integrates deep joint source and channel coding (DeepJSCC) with neural network-based digital modulation, enabling controlled jamming through two-layer superposition coding. The outer constellation sequence encodes the source image, while the inner constellation sequence, derived from a secret image, acts as the jamming signal. By minimizing the mutual information between the outer and inner constellation sequences, the jamming effect is enhanced. The jamming signal is superposed on the outer constellation sequence, preventing the eavesdropper from recovering the source image. The power allocation coefficient (PAC) in the superposition coding can be adjusted to control system security. Experiments show that our approach matches existing methods in security while significantly improving reconstruction performance across varying channel signal-to-noise ratios (SNRs) and compression ratios. Copyright © 2025, The Authors. All rights reserved.

关键词： Digital communication systems

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A Weighted Least-Squares Method for Non-Asymptotic Identification of Markov Parameters from Multiple Trajectories

arXiv

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arXiv 2024年

作者： He, Jiabao Rojas, Cristian R. Hjalmarsson, Håkan Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden

Markov parameters play a key role in system identification. There exists many algorithms where these parameters are estimated using least-squares in a first, pre-processing, step, including subspace identification and multi-step least-squares algorithms, such as Weighted Null-Space Fitting. Recently, there has been an increasing interest in non-asymptotic analysis of estimation algorithms. In this contribution we identify the Markov parameters using weighted least-squares and present non-asymptotic analysis for such estimator. To cover both stable and unstable systems, multiple trajectories are collected. We show that with the optimal weighting matrix, weighted least-squares gives a tighter error bound than ordinary least-squares for the case of non-uniformly distributed measurement errors. Moreover, as the optimal weighting matrix depends on the system’s true parameters, we introduce two methods to consistently estimate the optimal weighting matrix, where the convergence rate of these estimates is also provided. Numerical experiments demonstrate improvements of weighted least-squares over ordinary least-squares in finite sample settings. Copyright © 2024, The Authors. All rights reserved.

关键词： Asymptotic analysis

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Uncertainty-Informed Model Selection Method for Nonlinear System Identification and Interpretable Machine Learning

Uncertainty-Informed Model Selection Method for Nonlinear Sy...

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Mediterranean Conference on control and Automation (MED)

作者： Yuanlin Gu Hua-Liang Wei Division of Computer Science and Maths University of Stirling Stirling United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Sheffield

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

Modeling uncertainty has been an active and important topic in the fields of data-driven modeling and machine learning. Uncertainty ubiquitously exists in any data modeling process, making it challenging to identify the optimal models among many potential candidates. This article proposes an uncertainty-informed method to address the model selection problem. The performance of the proposed method is evaluated on a dataset generated from a complex system model. The experimental results demonstrate the effectiveness of the proposed method and its superiority over conventional approaches. This method has minimal requirements for the length of training data and model types, making it applicable for various modeling frameworks.

关键词： Data-driven modeling Adaptation models Uncertainty Recurrent neural networks Training data Machine learning Data models

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Evolution and Effectiveness of Loss Functions in Generative Adversarial Networks

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China Communications 2021年第10期18卷 45-76页

作者： Ali Syed Saqlain Fang Fang Tanvir Ahmad Liyun Wang Zain-ul Abidin School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China Department of Computer Science Portland State UniversityPortland 97207U.S. School of Information and Communication Engineering South West Jiaotong UniversityChengdu 610031China

Recently,the evolution of Generative Adversarial Networks(GANs)has embarked on a journey of revolutionizing the field of artificial and computational *** improve the generating ability of GANs,various loss functions are introduced to measure the degree of similarity between the samples generated by the generator and the real data samples,and the effectiveness of the loss functions in improving the generating ability of *** this paper,we present a detailed survey for the loss functions used in GANs,and provide a critical analysis on the pros and cons of these loss ***,the basic theory of GANs along with the training mechanism are ***,the most commonly used loss functions in GANs are introduced and ***,the experimental analyses and comparison of these loss functions are presented in different GAN ***,several suggestions on choosing suitable loss functions for image synthesis tasks are given.

关键词： loss functions deep learning machine learning unsupervised learning generative adversarial networks(GANs) image synthesis

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Application of Event-based Cloud NMPC with Time Delay Compensation

Application of Event-based Cloud NMPC with Time Delay Compen...

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Industrial Cyber-Physical Systems (ICPS)

作者： Alvin Immanuel Surjana Elmar Ahle Dirk Söffker Electrical Engineering and Computer Science University of Applied Sciences Niederrhein Krefeld Germany Dynamics and Control University of Duisburg-Essen Duisburg Germany

ISBN: (数字)9798350363012

ISBN: (纸本)9798350363029

The increasing availability of cloud computing services has revolutionized industrial productivity by providing essential tools for data storage, data transfer, and computation. In a cloud-based control system (CCS), the controller is located in the cloud, thereby enabling complex computation processes such as nonlinear model predictive control (NMPC). Using cloud computing, expensive control algorithms can be deployed without the upfront cost of a local computing unit. The computation time can be drastically reduced due to the improved computing power, which is important in the case of systems with fast dynamics in combination with NMPC-based control to maintain the existing time step size with regard to the calculation time. Placing the controller in the cloud also introduces communication latency in the control loop. It has been highlighted in former studies that computation time and communication latency can reduce the reliability and stability of a CCS. This paper proposes a cloud-based model predictive control strategy that extends simple time delay compensation with event-based control to reduce the effect of computation and communication delays. The optimal input variable sequence is used until a new sequence is available. This event-based method reduces the amount of communication and redundant calculations. The developed CCS algorithm is implemented in the real-time control of an experimental pendulum crane system. The effects of the proposed algorithm in mitigating computation and communication delay are compared to another CCS strategy that only uses the first element of the sequence.

关键词： Productivity Cloud computing Delay effects control systems Prediction algorithms Stability analysis Real-time systems

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HRPDF: A Software-Based Heterogeneous Redundant Proactive Defense Framework for Programmable Logic controller

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Journal of computer science & Technology 2021年第6期36卷 1307-1324页

作者： Ke Liu Jing-Yi Wang Qiang Wei Zhen-Yong Zhang Jun Sun Rong-Kuan Ma Rui-Long Deng State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001China College of Control Science and Engineering Zhejiang UniversityHangzhou 310027China College of Computer Science and Technology Guizhou UniversityGuiyang 550025China School of Information Systems Singapore Management UniversitySingapore 689867Singapore

Programmable logic controllers(PLCs)play a critical role in many industrial control systems,yet face increasingly serious cyber *** this paper,we propose a novel PLC-compatible software-based defense mechanism,called Heterogeneous Redundant Proactive Defense Framework(HRPDF).We propose a heterogeneous PLC architecture in HRPDF,including multiple heterogeneous,equivalent,and synchronous runtimes,which can thwart multiple types of attacks against PLC without the need of external *** ensure the availability of PLC,we also design an inter-process communication algorithm that minimizes the overhead of *** implement a prototype system of HRPDF and test it in a real-world PLC and an OpenPLC-based device,*** results show that HRPDF can defend against multiple types of attacks with 10.22%additional CPU and 5.56%additional memory overhead,and about 0.6 ms additional time overhead.

关键词： industrial control system programmable logic controller proactive defense heterogeneous redundant architecture

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Some Remarks on Fault-Tolerant Dynamic control Allocation for Weakly Redundant Systems

Some Remarks on Fault-Tolerant Dynamic Control Allocation fo...

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Mediterranean Conference on control and Automation (MED)

作者： Andrea Cristofaro Michelangelo Faleschini Department of Computer Control and Management Engineering Sapienza University of Rome Italy School of Science and Technology - Mathematics Division University of Camerino Italy

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

We consider the problem of control allocation for weakly redundant systems subject to actuator faults. In particular, the design of a suitable allocator will be devised with the aim of compensating for the fault effects while, at the same time, keeping the control burden as low as possible. To this goal, two approaches can be followed for the synthesis of the allocation servomechanism: direct allocation using orthogonal projection and optimization-based allocation. Some numerical examples illustrate and highlight advantages, disadvantages and limitations of both strategies.

关键词： Fault tolerance Actuators Automation Fault tolerant systems Dynamic scheduling Resource management Servomechanisms

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Automating the Generation of Functional Stress Inducing Stimuli for Burn-In Testing

Automating the Generation of Functional Stress Inducing Stim...

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IEEE European Test Symposium (ETS)

作者： Nikolaos I. Deligiannis Tobias Faller Zhou Chenghan Riccardo Cantoro Bernd Becker Matteo Sonza Reorda Department of Control and Computer Engineering (DAUIN) Politecnico di Torino Turin Italy Department of Computer Science University of Freiburg Freiburg Germany

In the domain of high reliability applications, Burn-In testing (BI) is always present since it is one of the prime countermeasures against the infant mortality phenomenon. Traditional static BI testing proves to be inefficient for modern circuit designs. As the devices’ feature size scales down and their structural and architectural complexity increases, so does the complexity and cost of the BI test. Different BI methods are employed by the industry where stimuli are also applied to the devices under test (DUTs) in order to effectively stress and stimulate all nets of the design. One known industry practice resorts to Design for Testability (DfT) infrastructures (e.g., scan) and is based on the application of test vectors at low frequency to excite the DUT as much as possible with the goal of switching each net of the design at least once. In this paper we consider the case where the layout of the circuit is known and propose two novel methods able to automatically produce functional stimuli to switch pairs of neighboring nodes (i.e., nodes that are placed within a specified distance in the DUT) in short periods of time. This solution has been shown to be able to trigger some latent defects in a circuit better than other methods. As a case study, we target functional units within a RISC-V processor (RI5CY). We show that the functional stimuli generated by the exact method described in the paper are able to achieve optimal results (i.e., the maximum functional switching of neighboring pairs), thus maximizing the chance that their at-speed application can activate weak points in the circuit.

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On final opinions of the Friedkin-Johnsen model over random graphs with partially stubborn community

On final opinions of the Friedkin-Johnsen model over random ...

引用

IEEE Conference on Decision and control

作者： Lingfei Wang Yu Xing Karl H. Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and with Digital Futures Stockholm Sweden

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper studies the formation of final opinions for the Friedkin-Johnsen (FJ) model with a community of partially stubborn agents. The underlying network of the FJ model is symmetric and generated from a random graph model, in which each link is added independently from a Bernoulli distribution. It is shown that the final opinions of the FJ model will concentrate around those of an FJ model over the expected graph as the network size grows, on the condition that the stubborn agents are well connected to other agents. Probability bounds are proposed for the distance between these two final opinion vectors, respectively for the cases where there exist non-stubborn agents or not. Numerical experiments are provided to illustrate the theoretical findings. The simulation shows that, in presence of non-stubborn agents, the link probability between the stubborn and the non-stubborn communities affect the distance between the two final opinion vectors significantly. Additionally, if all agents are stubborn, the opinion distance decreases with the agent stubbornness.

关键词： Vectors Numerical models

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