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A Survey of Cyber Attacks on Cyber Physical Systems:Recent Advances and Challenges

IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 784-800页

作者： Wenli Duo MengChu Zhou abdullah Abusorrah Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China IEEE Department of Electrical and Computer Engineering K.A.CARE Energy Research and Innovation Center Department of Electrical and Computer Engineering K.A.CARE Energy Research and Innovation Center and Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz University

A cyber physical system(CPS)is a complex system that integrates sensing,computation,control and networking into physical processes and objects over *** plays a key role in modern industry since it connects physical and cyber *** order to meet ever-changing industrial requirements,its structures and functions are constantly ***,new security issues have arisen.A ubiquitous problem is the fact that cyber attacks can cause significant damage to industrial systems,and thus has gained increasing attention from researchers and *** paper presents a survey of state-of-the-art results of cyber attacks on cyber physical ***,as typical system models are employed to study these systems,time-driven and event-driven systems are ***,recent advances on three types of attacks,i.e.,those on availability,integrity,and confidentiality are *** particular,the detailed studies on availability and integrity attacks are introduced from the perspective of attackers and ***,both attack and defense strategies are discussed based on different system *** challenges and open issues are indicated to guide future research and inspire the further exploration of this increasingly important area.

关键词： Attack detection attack strategy cyber attack cyber physical system(CPS) secure control

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A Novel Multiobjective Fireworks Algorithm and Its Applications to Imbalanced Distance Minimization Problems

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IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1476-1489页

作者： Shoufei Han Kun Zhu MengChu Zhou Xiaojing Liu Haoyue Liu Yusuf Al-Turki abdullah Abusorrah College of Computer Science and Technology Nanjing University of Aeronautics and Astronauticsand also with the Collaborative Innovation Center of Novel Software Technology and IndustrializationNanjing 211106China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of Engineeringand also with the K.A.CARE Energy Research and Innovation CenterKing Abdulaziz UniversityJeddah 21589Saudi Arabia

Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing *** goal is to find a Pareto front and as many equivalent Pareto optimal solutions as *** some evolutionary algorithms for them have been proposed,they mainly focus on the convergence rate in the decision space while ignoring solutions *** this paper,we propose a new multiobjective fireworks algorithm for them,which is able to balance exploitation and exploration in the decision *** first extend a latest single-objective fireworks algorithm to handle *** we make improvements by incorporating an adaptive strategy and special archive guidance into it,where special archives are established for each firework,and two strategies(i.e.,explosion and random strategies)are adaptively selected to update the positions of sparks generated by fireworks with the guidance of special ***,we compare the proposed algorithm with eight state-of-the-art multimodal multiobjective algorithms on all 22 MMOPs from CEC2019 and several imbalanced distance minimization *** results show that the proposed algorithm is superior to compared algorithms in solving ***,its runtime is less than its peers'.

关键词： Adaptive strategy fireworks algorithm multimodal multiobjective optimization problems(MMOP)

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Stochastic Geometry-Based Performance Evaluation for LEO Satellite-Assisted Space Caching

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IEEE Internet of Things Journal 2025年

作者： Ma, Chunyi Xu, Jiajie Yang, Jianhua Kishk, Mustafa A. Northwestern Polytechnical University School of Automation Xi’an710129 China King Abdullah University of Science and Technology Computer Electrical and Mathematical Science and Engineering Division Thuwal Saudi Arabia Maynooth University Department of Electronic Engineering Maynooth Ireland

To achieve the Internet of Things (IoT) vision, Mobile Edge Computing (MEC) is a promising technology aimed at providing low-latency computing services to user equipment (UE). However, terrestrial MEC network struggles to provide service to UEs in remote and maritime region. Low Earth Orbit (LEO) satellite networks have the potential to overcome geographical restrictions and provide seamless global coverage for UEs. In this paper, we provide the first attempt to use stochastic geometry to investigate the performance of implementing space caching with LEO satellites (SATs) in the MEC network. We study a LEO satellite-assisted space caching MEC network, and LEO SATs can be equipped with servers to enable space caching, with the advantage of seamless coverage to assist terrestrial CSs for serving UEs in remote or maritime reigon. Using stochastic geometry and queuing theory, we establish an analytical framework for this MEC network. Meanwhile, we develop association strategies for UEs to connect with LEO SATs or CSs and utilize stochastic geometry to derive uplink and downlink coverage probabilities, considering the diversity of task and service types. On this basis, we employ the queuing theory to calculate the average delay to evaluate the system performance. Through Monte Carlo simulations and numerical results, the system performance is evaluated. The results show the potential of SAT spatial caching in improving the performance of the MEC network. Additionally, our results reveal useful insights such as the significant impact of the altitude and number of LEO SATs on the average delay of the network, providing helpful systemlevel recommendations for the design and configuration of the space-caching MEC network. © 2014 IEEE.

关键词： Queueing theory

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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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computer Modeling in engineering & sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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A Joint Resource Allocation Algorithm for D2D Communication

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computers, Materials & Continua 2022年第2期70卷 3751-3762页

作者： Abdul Kadir Hamid Lamia Osman Widaa Fahd N.Al-Wesabi Imran Khan Anwer Mustafa Hilal Manar Ahmed Hamza Abu Sarwar Zaman Mohammed Rizwanullah Department of Electrical&Computer Engineering University of SharjahSharjahUnited Arab Emirates Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerKSA&Faculty of Computer and ITSana’a UniversityYemen Department of Electrical Engineering University of Engineering and Technology PeshawarPakistan Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The emergence of multimedia services has meant a substantial increase in the number of devices in mobile networks and driving the demand for higher data transmission *** result is that,cellular networks must technically evolve to support such higher rates,to be equipped with greater capacity,and to increase the spectral and energy *** with 4G technology,the 5G networks are being designed to transmit up to 100 times more data volume with devices whose battery life is 10 times ***,this new generation of networks has adopted a heterogeneous and ultra-dense architecture,where different technological advances are combined such as device-to-device(D2D)communication,which is one of the key elements of 5G *** has immediate applications such as the distribution of traffic load(data offloading),communications for emergency services,and the extension of cellular coverage,*** this communication model,two devices can communicate directly if they are close to each other without using a base station or a remote access ***,eliminating the interference between theD2Dand cellular communication in the *** interference management has become a hot issue in current *** order to address this problem,this paper proposes a joint resource allocation algorithm based on the idea of mode selection and resource *** results showthat the proposed algorithm effectively improves the systemperformance and reduces the interference as compared with existing algorithms.

关键词： D2D communication resource allocation wireless networks mobile communication

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End-to-End Learning of Beam Probing and RSSI-Based Multi-User Hybrid Precoding Design

End-to-End Learning of Beam Probing and RSSI-Based Multi-Use...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Asmaa Abdallah Abdulkadir Celik Ahmed Alkhateeb Ahmed M. Eltawil Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal KSA Department of Electrical Computer and Energy Engineering Arizona State University Tempe USA

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

This paper presents an end-to-end (E2E) autoencoder learning framework that relies on unsupervised deep learning for the joint design of millimeter wave (mmWave) probing beams and hybrid precoding matrices in multi-user communication systems. Our model utilizes prior channel observations to achieve two main objectives: designing a compact set of probing beams and predicting off-grid radio frequency (RF) beamforming vectors. The E2E learning framework optimizes probing beams in an unsupervised manner, concentrating sensing power on promising spatial directions based on the environment. To this aim, we develop a neural network architecture respecting RF chain constraints and model received signal strength (RSS) using complex-valued convolutional layers. The autoencoder is trained to directly produce RF beamforming vectors for hybrid architectures based on projected RSS indicators (RSSIs). Once RF beamforming vectors for multi-users are predicted, baseband digital precoders are designed by accounting for multi-user interference. The autoencoder neural network is trained E2E in an unsupervised manner with a customized loss function aimed at maximizing RSS. In a system with 64 antennas, 4 RF chains, and 4 users, our approach requires only 8 probing beams to design RF beamforming vectors, compared to the conventional predefined codebooks with 64 or 128 beams.

关键词： Radio frequency Array signal processing Precoding Autoencoders Neural networks Millimeter wave technology Interference Predictive models Vectors Millimeter wave communication

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Non-Contact Acquisition of PPG Signal using Chest Movement-Modulated Radio Signals

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IFAC-PapersOnLine 2024年第24期58卷 579-583页

作者： Israel Jesus Santos Filho Muhammad Mahboob Ur Rahman Taous-Meriem Laleg-Kirati Tareq Al-Naffouri Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE) King Abdullah University of Science and Technology Thuwal 23955 Saudi Arabia The National Institute for Research in Digital Science and Technology Paris-Saclay France

We present for the first time a novel method that utilizes the chest movement-modulated radio signals for non-contact acquisition of the photoplethysmography (PPG) signal. Under the proposed method, a software-defined radio (SDR) exposes the chest of a subject sitting nearby to an orthogonal frequency division multiplexing signal with 64 sub-carriers at a center frequency 5.24 GHz, while another SDR in the close vicinity collects the modulated radio signal reflected of the chest. This way, we construct a custom dataset by collecting 160 minutes of labeled data (both raw radio data as well as the reference PPG signal) from 16 healthy young subjects. With this, we first utilize principal component analysis for dimensionality reduction of the radio data. Next, we denoise the radio signal and reference PPG signal using wavelet technique, followed by segmentation and Z-score normalization. We then synchronize the radio and PPG segments using cross-correlation method. Finally, we proceed to the waveform translation (regression) task, whereby we first convert the radio and PPG segments into frequency domain using discrete cosine transform (DCT), and then learn the non-linear regression between them. Eventually, we reconstruct the synthetic PPG signal by taking inverse DCT of the output of regression block, with a mean absolute error of 8.1294. The synthetic PPG waveform has a great clinical significance as it could be used for non-contact performance assessment of cardiovascular and respiratory systems of patients suffering from infectious diseases, e.g., covid19.

关键词： Non-contact methods RF-based methods software-defined radio PPG deep learning

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DNBP-CCA:A Novel Approach to Enhancing Heterogeneous Data Traffic and Reliable Data Transmission for Body Area Network

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computers, Materials & Continua 2024年第5期79卷 2851-2878页

作者： Abdulwadood Alawadhi Mohd.Hasbullah Omar abdullah Almogahed Noradila Nordin Salman A.Alqahtani Atif M.Alamri InterNetWorks Research Laboratory School of ComputingUniversiti Utara MalaysiaSintok06010Malaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaParit RajaJohor86400Malaysia School of Games&Creative Technology University for the Creative ArtsFarnhamGU97DSUK Computer Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

The increased adoption of Internet of Medical Things (IoMT) technologies has resulted in the widespread use ofBody Area Networks (BANs) in medical and non-medical domains. However, the performance of IEEE 802.15.4-based BANs is impacted by challenges related to heterogeneous data traffic requirements among nodes, includingcontention during finite backoff periods, association delays, and traffic channel access through clear channelassessment (CCA) algorithms. These challenges lead to increased packet collisions, queuing delays, retransmissions,and the neglect of critical traffic, thereby hindering performance indicators such as throughput, packet deliveryratio, packet drop rate, and packet delay. Therefore, we propose Dynamic Next Backoff Period and Clear ChannelAssessment (DNBP-CCA) schemes to address these issues. The DNBP-CCA schemes leverage a combination ofthe Dynamic Next Backoff Period (DNBP) scheme and the Dynamic Next Clear Channel Assessment (DNCCA)scheme. The DNBP scheme employs a fuzzy Takagi, Sugeno, and Kang (TSK) model’s inference system toquantitatively analyze backoff exponent, channel clearance, collision ratio, and data rate as input parameters. Onthe other hand, the DNCCA scheme dynamically adapts the CCA process based on requested data transmission tothe coordinator, considering input parameters such as buffer status ratio and acknowledgement ratio. As a result,simulations demonstrate that our proposed schemes are better than some existing representative approaches andenhance data transmission, reduce node collisions, improve average throughput, and packet delivery ratio, anddecrease average packet drop rate and packet delay.

关键词： Internet of Medical Things body area networks backoff period tsk fuzzy model clear channel assessment media access control

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On the Optimal Expressive Power of ReLU DNNs and Its Application in Approximation with Kolmogorov Superposition Theorem

arXiv

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arXiv 2023年

作者： He, Juncai Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

This paper is devoted to studying the optimal expressive power of ReLU deep neural networks (DNNs) and its application in approximation via the Kolmogorov Superposition Theorem. We first constructively prove that any continuous piecewise linear functions on [0, 1], comprising O(N2L) segments, can be represented by ReLU DNNs with L hidden layers and N neurons per layer. Subsequently, we demonstrate that this construction is optimal regarding the parameter count of the DNNs, achieved through investigating the shattering capacity of ReLU DNNs. Moreover, by invoking the Kolmogorov Superposition Theorem, we achieve an enhanced approximation rate for ReLU DNNs of arbitrary width and depth when dealing with continuous functions in high-dimensional *** Codes 41A30, 68T07, 65D40 Copyright © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

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An Explicit Discontinuous Galerkin Time-Domain Scheme to Simulate Kerr Nonlinearity

An Explicit Discontinuous Galerkin Time-Domain Scheme to Sim...

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Antennas and Propagation Society International Symposium

作者： Ruitao Sun Ming Dong Liang Chen Hakan Bagci Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

A discontinuous Galerkin time-domain (DGTD) method is formulated and implemented to analyze transient electromagnetic field interactions in a medium with Kerr nonlinearity. The (nonlinear) Maxwell equations in conservative form are discretized using a DG scheme that employs the Harten-Lax-van Leer numerical flux to facilitate the information exchange between discretization elements. A slope limiter is introduced into the DGTD method to prevent generation of non-physical oscillations in the solution and maintain the stability of the explicit time marching. Numerical examples, which demonstrate the applicability and the accuracy of the proposed method, are presented.

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