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Industrial Control Anomaly Detection Based on Distributed Linear Deep Learning

computers, Materials & Continua 2025年第1期82卷 1129-1150页

作者： Shijie Tang Yong Ding Huiyong Wang School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin541004China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin541004China Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China Institute of Cyberspace Technology HKCT Institute for Higher EducationHong Kong999077China School of Mathematics&Computing Science Guilin University of Electronic TechnologyGuilin541004China

As more and more devices in Cyber-Physical Systems(CPS)are connected to the Internet,physical components such as programmable logic controller(PLC),sensors,and actuators are facing greater risks of network attacks,and fast and accurate attack detection techniques are *** key problem in distinguishing between normal and abnormal sequences is to model sequential changes in a large and diverse field of time *** address this issue,we propose an anomaly detection method based on distributed deep *** method uses a bilateral filtering algorithm for sequential sequences to remove noise in the time series,which can maintain the edge of discrete *** use a distributed linear deep learning model to establish a sequential prediction model and adjust the threshold for anomaly detection based on the prediction error of the validation *** method can not only detect abnormal attacks but also locate the sensors that cause *** conducted experiments on the Secure Water Treatment(SWAT)and Water Distribution(WADI)public *** experimental results show that our method is superior to the baseline method in identifying the types of attacks and detecting efficiency.

关键词： Anomaly detection CPS deep learning MLP(multi-layer perceptron)

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Machine Learning for Data Fusion:A Fuzzy AHP Approach for Open Issues

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computers, Materials & Continua 2023年第12期77卷 2899-2914页

作者： Vinay Kukreja Asha Abraham K.Kalaiselvi K.Deepa Thilak Shanmugasundaram Hariharan Shih-Yu Chen Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjab140401India Department of Networking and Communications SRM Institute of Science and TechnologyKattankulathurChengalpattuTamil Nadu603203India Department of Networking and Communications Faculty of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathurChengalpattuTamil Nadu603203India Department of Computer Science and Engineering Vardhaman College of EngineeringHyderabad501218India Department of Computer Science and Information Engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Intelligence Recognition Industry Service Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan

Data fusion generates fused data by combining multiple sources,resulting in information that is more consistent,accurate,and useful than any individual source and more reliable and consistent than the raw original data,which are often imperfect,inconsistent,complex,and *** data fusion methods like probabilistic fusion,set-based fusion,and evidential belief reasoning fusion methods are computationally complex and require accurate classification and proper handling of raw *** fusion is the process of integrating multiple data *** filtering means examining a dataset to exclude,rearrange,or apportion data according to the *** sensors generate a large amount of data,requiring the development of machine learning(ML)algorithms to overcome the challenges of traditional *** advancement in hardware acceleration and the abundance of data from various sensors have led to the development of machine learning(ML)algorithms,expected to address the limitations of traditional ***,many open issues still exist as machine learning algorithms are used for data *** the literature,nine issues have been identified irrespective of any *** decision-makers should pay attention to these issues as data fusion becomes more applicable and successful.A fuzzy analytical hierarchical process(FAHP)enables us to handle these *** helps to get the weights for each corresponding issue and rank issues based on these calculated *** most significant issue identified is the lack of deep learning models used for data fusion that improve accuracy and learning quality weighted *** least significant one is the cross-domain multimodal data fusion weighted 0.076 because the whole semantic knowledge for multimodal data cannot be captured.

关键词： Signal level fusion feature level fusion decision level fusion fuzzy hierarchical process machine learning

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Fractional Linear Matroid Matching Is in Quasi-NC 32

Fractional Linear Matroid Matching Is in Quasi-NC

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32nd Annual European Symposium on Algorithms, ESA 2024

作者： Gurjar, Rohit Oki, Taihei Raj, Roshan Department of Computer Science and Engineering Indian Institute of Technology Bombay Mumbai India Department of Mathematical Informatics Graduate School of Information Science and Technology The University of Tokyo Japan

ISBN: (纸本)9783959773386

The matching and linear matroid intersection problems are solvable in quasi-NC, meaning that there exist deterministic algorithms that run in polylogarithmic time and use quasi-polynomially many parallel processors. However, such a parallel algorithm is unknown for linear matroid matching, which generalizes both of these problems. In this work, we propose a quasi-NC algorithm for fractional linear matroid matching, which is a relaxation of linear matroid matching and commonly generalizes fractional matching and linear matroid intersection. Our algorithm builds upon the connection of fractional matroid matching to non-commutative Edmonds' problem recently revealed by Oki and Soma (2023). As a corollary, we also solve black-box non-commutative Edmonds' problem with rank-two skew-symmetric coefficients. © Rohit Gurjar, Taihei Oki, and Roshan Raj;licensed under Creative Commons License CC-BY 4.0.

关键词： Parallel algorithms

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Investigation of Scalable Approximation of the Minimum Variance Distortionless Response Beamformer

Investigation of Scalable Approximation of the Minimum Varia...

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2024 IEEE International Symposium on Phased Array Systems and technology, ARRAY 2024

作者： Park, Jung-Jin Rodriguez-Martinez, Gumer Bolding, Mark M. Westafer, Ryan S. Sathe, Visvesh S. School of Electrical and Computer Engineering Georgia Institute of Technology United States Georgia Tech Research Institute Georgia Institute of Technology Information and Communications Laboratory United States

ISBN: (纸本)9798350392142

The minimum variance distortionless response (MVDR) beamformer is commonly used with phased arrays to perform adaptive spatial filtering - preserving array gain in a desired direction while minimizing in-band interference from other directions. This constrained optimization problem is traditionally solved by regularly constructing and inverting the array covariance matrix, resulting in computational complexity of order O(N3), where N is the number of elements in the array. This paper explores a beamspace approximation, using a combination of the spatial fast Fourier transform (FFT) and iterative search, to achieve linear-logarithmic complexity. We investigate the signal to interference-plus-noise ratio (SINR) and complexity tradeoffs associated with this approach to examine its suitability for large array systems, © 2024 IEEE.

关键词： Constrained optimization

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Study of RSSI and Throughput in Identical Residential Units with Various Wi-Fi Configurations 10

Study of RSSI and Throughput in Identical Residential Units ...

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10th International Conference on Signal Processing and Communication, ICSC 2025

作者： Kumar, Varun Somani, Sakshi Jarupla, Hari Gopal Indian Institute of Information Technology Vadodara - International Campus Diu Department of Computer Science and Engineering India

ISBN: (纸本)9798331511890

Indoor communication is very popular in residential and office environment for the users with low mobility. Wireless signals are significantly affected by various obstructing materials and surfaces. This paper presents a study measuring the received signal strength indicator (RSSI) and throughput in a typical 3BHK residential unit. The propagation scenarios are line-of-sight (LoS), obstructed LoS (OLoS) and non-line-of-sight (NLoS). The operating frequency band of transmitted wireless signal is sub 6GHz band. We placed some more obstructing material inside the flat and analyzed the receiver performance in terms of RSSI and Throughput. The study observed a relationship between RSSI and throughput across different propagation scenarios and found that, in some cases, the performance under OLoS conditions was superior to that of LoS. © 2025 IEEE.

关键词： Fresnel zone Indoor propagation RSSI Throughput

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Proposed Biometric Security System Based on Deep Learning and Chaos Algorithms

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computers, Materials & Continua 2023年第2期74卷 3515-3537页

作者： Iman Almomani Walid El-Shafai Aala AlKhayer Albandari Alsumayt Sumayh S.Aljameel Khalid Alissa Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Computer Science Department King Abdullah II School of Information TechnologyThe University of Jordan11942Jordan Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Computer Science Department Applied CollegeImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Computer Science Department College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia SAUDI ARAMCO Cybersecurity Chair Networks and Communications DepartmentCollege of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

Nowadays,there is tremendous growth in biometric authentication and cybersecurity ***,the efficient way of storing and securing personal biometric patterns is mandatory in most governmental and private ***,designing and implementing robust security algorithms for users’biometrics is still a hot research area to be *** work presents a powerful biometric security system(BSS)to protect different biometric modalities such as faces,iris,and *** proposed BSSmodel is based on hybridizing auto-encoder(AE)network and a chaos-based ciphering algorithm to cipher the details of the stored biometric patterns and ensures their *** employed AE network is unsupervised deep learning(DL)structure used in the proposed BSS model to extract main biometric *** obtained features are utilized to generate two random chaos *** first random chaos matrix is used to permute the pixels of biometric *** contrast,the second random matrix is used to further cipher and confuse the resulting permuted biometric pixels using a two-dimensional(2D)chaotic logisticmap(CLM)*** assess the efficiency of the proposed BSS,(1)different standardized color and grayscale images of the examined fingerprint,faces,and iris biometrics were used(2)comprehensive security and recognition evaluation metrics were *** assessment results have proven the authentication and robustness superiority of the proposed BSSmodel compared to other existing *** example,the proposed BSS succeeds in getting a high area under the receiver operating characteristic(AROC)value that reached 99.97%and low rates of 0.00137,0.00148,and 3516 CMC,2023,vol.74,no.20.00157 for equal error rate(EER),false reject rate(FRR),and a false accept rate(FAR),respectively.

关键词： Biometric security deep learning AE network 2D CLM cybersecurity and authentication applications feature extraction unsupervised learning

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Fault-Localization in Water Distribution Networks using Hierarchical Anomaly Analysis 27

Fault-Localization in Water Distribution Networks using Hier...

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27th International computer Conference, computer Society of Iran, CSICC 2022

作者： Mirzaie, Sara Bushehrian, Omid Shiraz University Of Technology Department Of Computer Engineering And Information Technology Shiraz Iran

ISBN: (纸本)9781665480277

Water Distribution Networks (WDN) are vulnerable to unexpected events of the environment, system aging and security attacks. Real-time monitoring of WDNs is essential to detect disruptions, localize faulty elements and make fast decisions. Various anomaly detection methods are used to detect abnormal behaviors at these systems. One important challenge is to find a proper computing architecture for analyzing the collected sensory data from WDN in order to accurately localize the faulty element in the network that caused the anomalous behavior. We created an urban Water Distribution Network dataset using Epanet2w simulator software by measuring WDN hydraulic features: pressure and head. We added several distinct events (unexpected behavior) with different scales during the simulation time. To evaluate the impact of the computing architectures on the accuracy of fault localization, we examined several architectures: Centralized Cloud Architecture (CCA), three-layer Fog Computing Architecture (FGA) and the proposed Hierarchical Architecture (HA). The data and computing nodes at different layers were executed as docker containers with limited resources. The evaluation results showed a significant increase in fault localization accuracy using the proposed HA compared to other architectures. © 2022 IEEE.

关键词： Location awareness computer architecture Distribution networks Software Real-time systems Behavioral sciences Pressure measurement

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A Comparative Analysis of Artificial Neural Networks in Time Series Forecasting Using Arima Vs Prophet

A Comparative Analysis of Artificial Neural Networks in Time...

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2024 International Conference on Communication, computer Sciences and engineering, IC3SE 2024

作者： Anand, Pooja Sharma, Mayank Saroliya, Anil Amity Institute Of Information Technology Amity University Uttar Pradesh Noida India Mody University Of Science And Technology Department Of Computer Science Engineering Rajasthan Sikar India

ISBN: (纸本)9798350366846

Artificial intelligence heavily relies on neural networks, which enable machines to acquire knowledge and make informed choices by processing data inputs. Time series analysis plays a crucial role in enhancing the capabilities of AI systems powered by artificial neural networks (ANNs). This report provides an overview of neural networks, including the basic components, different types, and the training process. The report also explores advanced topics in neural networks, such as transfer learning, generative adversarial networks, and reinforcement learning. Finally, the report concludes by discussing the advancements and challenges in the field, as well as the future trends and prospects for neural networks. The report provides a comprehensive understanding of this complex but crucial aspect of AI. The aim of this piece is to introduce the concept of time series analysis using artificial neural networks and how it can be a powerful tool for modelling and forecasting complex temporal data. This article is targeted towards individuals with basic knowledge of statistics or machine learning who are interested in learning about time series analysis and its application in artificial neural networks. The focus of this article will be on explaining the fundamentals of time series analysis, exploring the capabilities and limitations of artificial neural networks in analyzing temporal data, and providing examples or case studies showcasing their effectiveness. The tone should be informative, clear, and accessible. Avoid jargon as much as possible while ensuring that technical terms are explained. Use examples to illustrate key concepts whenever appropriate. © 2024 IEEE.

关键词： Time series analysis

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Investigating Network and System Performance with Molecular Communication in Network Coding for Wireless Applications

Investigating Network and System Performance with Molecular ...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Rengarajan, A. Jain, Sandeep Kumar Rastogi, Ajay Department of Computer Science and Information Technology Bangalore India Vivekananda Global University Department of Electrical Engineering Jaipur India Teetthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India

ISBN: (纸本)9798350383348

This paper explores the effectiveness of molecular verbal exchange in network Coding (NC) for enhancing community overall performance in Wi-Fi applications. Molecular communique (MC) is an emerging nanoscale verbal exchange approach that allows efficient and dependable transmission of information and indicators over Wi-Fi. By utilizing the variety of molecules, the performance of molecular communique can be appreciably multiplied. This paper examines how network Coding with molecular communication may be applied to improve network performance. Using a case evaluates the efficacy of this approach by looking at a wireless sensor community deployed in a temperate indoor environment. Consequences display growth in facts fee of as much as 30%, indicating a potential development in network performance via using network Coding with molecular conversation. The paper additionally discusses how network Coding can improve community safety, records accuracy, and general latency. Those potential upgrades are promising and future studies are needed to prove the effectiveness of community Coding with molecular verbal exchange in wireless applications. Molecular communique in community coding has emerged as a critical studies place due to its potential to enhance the bodily-layer overall performance of wireless networks. This paper evaluates the community and gadget's overall performance with molecular conversation in community coding for Wi-Fi packages. A theoretical evaluation, pc simulations, and experiments examine the gadget's performance. Moreover, the consequences of diverse parameters such as channel length, range of relay nodes, number of symbols transmitted, and coding fee are evaluated. The results imply that the overall performance of molecular conversation in network coding is superior to regular bodily-layer coding strategies, providing improved community throughput and conversation reliability. Additionally, the power efficiency of the proposed gadget is likewise tes

关键词： appreciably communique community multiplied topologies

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Analytic Beta-Wavelet Transform-Based Digital Image Watermarking for Secure Transmission

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computers, Materials & Continua 2022年第3期70卷 4657-4673页

作者： Hesham Alhumyani Ibrahim Alrube Sameer Alsharif Ashraf Afifi Chokri Ben Amar Hala S.El-Sayed Osama S.Faragallah Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityP.O.11099Taif21944Saudi Arabia Department of Electrical Engineering Faculty of EngineeringMenoufia UniversityShebin El-Kom32511Egypt Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.11099Taif21944Saudi Arabia

The rapid development in the information technology field has introduced digital watermark technologies as a solution to prevent unauthorized copying and redistribution of *** article introduces a self-embedded image verification and integrity *** images are firstly split into dedicated segments of the same block ***,different Analytic Beta-Wavelet(ABW)orthogonal filters are utilized for embedding a self-segment watermark for image segment using a predefined *** orthogonal filter coefficients are estimated to improve image reconstruction under different block *** conduct a comparative study comparing the watermarked images using three kinds of ABW filters for block sizes 64×64,128×128,and 256×*** embed the watermark using the ABW-based image watermarking method in the 2-level middle frequency sub-bands of the ABW digital image *** imperceptibility and robustness of the ABW-based image watermarking method image is evaluated based on the Peak Signal to Noise Ratio(PSNR)and Correlation coefficient *** the implementation results,we came to know that this ABW-based image watermarking method can withstand many image manipulations compared to other existing methods.

关键词： Watermarking ABW median filtering JPEG compression PSNR

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