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2023 Congress in computer science, computer engineering, and applied Computing, CSCE 2023

作者： Wang, Zichun Temesgen, Samuel Wu, Fred West Virginia State University Institute Department of Math Engineering and Computer Science United States

ISBN: (纸本)9798350327595

To cope with the growing number and changing nature of malicious cyber-attacks, machine learning techniques have been extensively employed to develop intrusion detection systems (IDS) for intelligent detection. However, these systems face numerous challenges, given the continually evolving nature of these attacks and their sheer volume. In here, a new hybrid intelligent IDS employing a combination of Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) is proposed. This model aims to classify audit data and predict potential security breaches by leveraging the strengths of both CNN and LSTM. The new hybrid model has shown a significant improvement in detection accuracy while reducing the detection time. © 2023 IEEE.

关键词： CNN Deep Learning IDS LSTM R1CIDS

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Enhancing the Robustness of Model-Predictive Control using GMMs as Outlier Detection 12

Enhancing the Robustness of Model-Predictive Control using G...

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12th IEEE International Conference on Intelligent Systems, IS 2024

作者： Féret, Leander J. Gepperth, Alexander Lambeck, Steven Jumo GmbH & Co. Kg Think Tank Fulda Germany Fulda University of Applied Sciences Applied Computer Science Department Fulda Germany Fulda University of Applied Sciences Electrical Engineering Department Fulda Germany

ISBN: (纸本)9798350350982

This article proposes a flexible control strategy to improve the reliability of data-driven model-predictive control (MPC). Prediction models are usually trained on logged data, which may be incomplete, leading to model failure within the optimization algorithm of the MPC. To counter this, we propose a Gaussian Mixture Model (GMM) for detecting outliers during live operation. These outliers are found in the observed system states as well as the calculated control signals regarding the logged training data of the ai-model. If an outlier is detected, we assume that the data-driven prediction model will be inaccurate, and an appropriate fallback strategy is used instead, which includes but is not limited to an alternative controller or a complete system-shutdown. In addition, outliers are stored for subsequent improvement of the prediction model. This outlier-protected control (OPC) architecture is evaluated in terms of control quality using the integrated squared error (ISE) on three nonlinear dynamical systems. The outcomes indicate a significant enhancement in control quality in comparison to an unprotected but otherwise equivalent architecture. These findings suggest that a very simple and efficient outlier detection can greatly benefit data-driven MPC in general whenever feasible fallback strategies exist. © 2024 IEEE.

关键词： Prediction models

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Internet of Things (IoT) in Smart Cities: A Statistical Survey 2

Internet of Things (IoT) in Smart Cities: A Statistical Surv...

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Iqbal, Muhammad Waseem Khaliq, Khowla Al-Dmour, Nidal A. Aqeel, Muhammad Ali, Nasir Hamid, K. Superior University Department of Software Engineering Lahore54000 Pakistan Superior University Department of Computer Sciecnce Lahore54000 Pakistan Mutah University College of Engineering Department of Computer Engineering Jordan NCBA&E School of Computer Science Lahore Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan

ISBN: (纸本)9798350335644

Internet of things is progressing very rapidly and involving multiple domains of everyday life including environment, governance, healthcare system, transportation system, energy management system, etc. smart city is a platform for collecting and storing the information that is accessed through various sensor-based IoT devices and make their information available in required and authorized domains. This interoperability can be achieved by semantic web technology. In this paper, I have reviewed multiple papers related to IoT in Smart Cities and presented a comparison among the semantic parameters. Moreover, I've presented my future domain of research which is about delivering the COVID-19 patients report to the concerned domains by the healthcare system domain. © 2023 IEEE.

关键词： Internet of things

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Computational Efficiency of Deep Learning-Based Super Resolution Methods for 5G-NR Channel Estimation

Computational Efficiency of Deep Learning-Based Super Resolu...

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2024 IEEE Latin-American Conference on Communications, LATINCOM 2024

作者： Goez, David Beyazit, Esra A. Slamnik-Krijestorac, Nina Marquez-Barja, Johann M. Gaviria, Natalia Latre, Steven Camelo, Miguel University of Antwerp - imec IDLab - Department of Computer Science Belgium Universidad de Antioquia Electronics Engineering Department Colombia University of Antwerp - imec IDLab - Faculty of Applied Engineering Belgium

ISBN: (纸本)9798331521110

The increasing demand for high-quality and efficient Channel Estimation (CE) in 5G New Radio (5G-NR) systems has prompted the exploration of advanced Deep Learning (DL) techniques. While traditional methods, such as Linear Interpolation (LI) and Least Squares (LS), provide reasonable accuracy and are practical for real-time physical layer processing, recent DL-based CE approaches have primarily focused on accuracy, often without evidence of real-time capabilities. In this paper, we present a comprehensive evaluation of DL-based Super-resolution (SR) methods for CE, comparing models like Super Resolution Convolutional Neural Network (SRCNN), ChannelNet, and Enhanced Deep Super-Resolution (EDSR) in both 1D and 2D convolutional architectures. We optimize these models using NVIDIA TensorRT to reduce computational complexity and latency. Our results show that the optimized 1D-EDSR model achieves the best performance with a Mean Squared Error (MSE) of 0.0126, outperforming all other models in terms of accuracy. However, the optimized 1D-EDSR model fails to meet real-time constraints due to additional computational overhead (0.6798 ms/sample). In contrast, the 1D-SRCNN model offers a balanced trade-off between MSE (0.01738) and inference time (0.0866ms/sample), achieving 40% higher accuracy than LS (0.0288) while maintaining the best energy efficiency (1.48 mJ/sample). © 2024 IEEE.

关键词： Mean square error

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Use of Polygram Substitution in Spotting the Swindler in Secret Sharing 11th

Use of Polygram Substitution in Spotting the Swindler in Sec...

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11th International Conference on Intelligent Computing and Applications, ICRTC 2023

作者： Yadav, Poonam Satheesh Kumar, S. Muthukumaran, V. Sandeep Kumar, mathivanan Radhika, E.K. Department of Computer Science School of Applied Sciences Reva University Bangalore India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur 603203 India School of Computer Science and Engineering Galgotias University Uttar Pradesh Greater Noida203201 India Department of Computer Science and Applications Sindhi College Bangalore560024 India

ISBN: (纸本)9789819717231

In the polygram substitution, one set of characters is replaced by another set based on algorithm. The model is proposed for calculating and estimating secure online secret shares, where dynamic modification in any of the shares will be identified if number of the shares are more than specified threshold value. The security is based on the intractability of factoring as it uses Lagrange polynomial function. This is further enhanced by a graphical masking and unmasking technique;it includes two phases: encryption of the individual secrets and sharing of the data. The generation of the shares is done by masking using Polygram substitution, and the shares are regenerated and unmasking of the qualified shares is done to find original secret. Masking is done on original secret, then shares are generated. Each encrypted share contains information which is different than original secret. Masking by Polygram substitution gives additional protection of secret data on the Internet. Moreover, we achieve efficient recovery of the original secret data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Polynomials

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Cyber Security Threats on Multifunctional Devices and Mitigation Techniques 2

Cyber Security Threats on Multifunctional Devices and Mitiga...

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Al-Dmour, Nidal A. Farooq, Umer Sarwar, Irfan Iqbal, Muhammad Waseem Aqeel, Muhammad Khan, Wasim Ahmad Al Hamadi, Hussam Mutah University College of Engineering Department of Computer Engineering Jordan LGU Department of Computer Science Lahore Pakistan Superior University Department of Computer Science Lahore54000 Pakistan Superior University Department of Software Engineering Lahore54000 Pakistan NCBA&E Lahore School of Computer Science Pakistan Applied Science Research Center Applied Science Private University Amman11937 Jordan University of Dubai College of Engineering and IT PO Box 14143 United Arab Emirates

ISBN: (纸本)9798350335644

The risks discussed in this document are related to smart printers/ fax/ photocopiers/ or e-mail-enabled smart devices, also known as "document centers,". These devices can be purchased outright or rented every month. When an item reaches its end of life, it is either donated to a non-profit organization or returned to the manufacturer (OEM) or supplier at the end of a lease arrangement. These network-interconnected devices have an inherent susceptibility that most IT operations teams or information security professionals are unaware of. This effort will raise awareness of the dangers of losing a company's data. This discussion will focus on reported vulnerabilities, previous discussions, and given the author's view on the potential danger. Create instructions for potential users on how to use and disassemble these devices safely to prevent losing sensitive data. Lastly, the technological structure of two potential attack vectors against a document center of an organization will be demonstrated in this study. The study was conducted in government as well as the private sector, medium-sized enterprises (300 employees of each entity) settings, outside of normal business hours, with special authorizations and engagement, limiting the scope to a minimal set of devices. © 2023 IEEE.

关键词： Sensitive data

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Detection of Osteoarthritis Based on EHO Thresholding

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computers, Materials & Continua 2022年第6期71卷 5783-5798页

作者： R.Kanthavel R.Dhaya Kanagaraj Venusamy Department of Computer Engineering King Khalid UniversityAbhaSaudi Arabia Department of Computer Science King Khalid UniversitySarat Abidha CampusAbhaSaudi Arabia Department of Engineering University of Technology and Applied SciencesAl MussanahSultanate of Oman

Knee Osteoarthritis(OA)is a joint disease that is commonly observed in people around the *** commonly affects patients who are obese and those above the age of 60.A valid knee image was generated by Computed Tomography(CT).In this work,efficient segmentation of CT images using Elephant Herding Optimization(EHO)optimization is *** initial stage employs,the CT image normalization and the normalized image is incited to image enhancement through histogram ***,the enhanced image is segmented by utilizing Niblack and Bernsen ***(EHO)optimized outcome is evaluated in two *** initial step includes image enhancement with the measure of Mean square error(MSE),Peak signal to noise ratio(PSNR)and Structural similarity index(SSIM).The following step includes the segmentation which includes the measure ofAccuracy,Sensitivity and *** comparative analysis of EHO provides 95%of accuracy,94%of specificity and 93%of sensitivity than that of Active contour and Otsu threshold.

关键词： Osteoarthritis CT images correlation histogram thresholding Niblack&Bernsen algorithm EH optimization

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Automatic Segmentation and Detection System for Varicocele Using Ultrasound Images

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computers, Materials & Continua 2022年第7期72卷 797-814页

作者： Ayman M.Abdalla Mohammad Abu Awad Omar AlZoubi La’aly A.Al-Samrraie Department of Computer Science Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science Jordan University of Science and TechnologyIrbid22110Jordan Department of Water and Environmental Engineering Al-Huson University CollegeAl-Balqa Applied UniversityIrbidJordan

The enlarged veins in the pampiniform venous plexus,known as varicocele disease,are typically identified using ultrasound *** diagnosis of varicocele is based on examinations made in three positions taken to the right and left testicles of the male *** proposed system is designed to determine whether a patient is *** is more frequent on the left side of the scrotum than on the right and physicians commonly depend on the supine position more than other ***,the experimental results of this study focused on images taken in the supine position of the left testicles of *** are two possible vein structures in each image:a cross-section(circular)and a tube(non-circular)*** proposed system identifies dilated(varicocele)veins of these structures in ultrasound images in three stages:preprocessing,processing,and detection and *** three stages are applied in three different color modes:Grayscale,Red-Green-Blue(RGB),and Hue,Saturation,and Value(HSV).In the preprocessing stage,the region of interest enclosing the pampiniform plexus area is extracted using a median filter and threshold ***,the processing stage employs different filters to perform image ***,edge detection is applied in multiple steps and the detected veins are measured to determine if dilated veins *** implementation results showed the proposed system is faster andmore effective than the previous work.

关键词： Varicocele color mode HSV median filter segmentation canny

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Estimating Risk-aware Flexibility Areas for Electric Vehicle Charging Pools via AC Stochastic Optimal Power Flow

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Journal of Modern Power Systems and Clean Energy 2023年第4期11卷 1247-1256页

作者： Juan S.Giraldo Nataly Bañol Arias Pedro P.Vergara Maria Vlasiou Gerwin Hoogsteen Johann L.Hurink Energy Transition Studies Group Netherlands Organisation for Applied Scientific Research(TNO)Amsterdam1043 NTThe Netherlands Department of Electrical Engineering Mathematics and Computer ScienceUniversity of TwenteEnschede7522 NBThe Netherlands Intelligent Electrical Power Grids Group Electrical EngineeringMathematics and Computer ScienceDelft University of TechnologyDelft2628 CDThe Netherlands

This paper introduces an AC stochastic optimal power flow(SOPF)for the flexibility management of electric vehicle(EV)charging pools in distribution networks under *** AC SOPF considers discrete utility functions from charging pools as a compensation mechanism for eventual energy not served to their charging *** application of the AC SOPF is described where a distribution system operator(DSO)requires flexibility to each charging pool in a day-ahead time frame,minimizing the cost for flexibility while guaranteeing technical *** areas are defined for each charging pool and calculated as a function of a risk parameter involving the uncertainty of the *** show that all players can benefit from this approach,i.e.,the DSO obtains a riskaware solution,while charging pools/tasks perceive a reduction in the total energy payment due to flexibility services.

关键词： Electric vehicle flexibility management stochastic optimal power flow(SOPF) risk awareness compensation mechanism

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Terahertz deep learning fusion computed tomography

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Optics Express 2024年第10期32卷 17763-17774页

作者： Hung, Yi-Chun Su, Weng-Tai Chao, Ta-Hsuan Lin, Chia-Wen Yang, Shang-Hua Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan Department of Computer Science McCormick School of Engineering and Applied Science Northwestern University EvanstonIL60208 United States Institute of Electronics Engineering National Tsing Hua University Hsinchu30013 Taiwan Terahertz Optics and Photonics Center National Tsing Hua University Hsinchu30013 Taiwan

Terahertz (THz) tomographic imaging based on time-resolved THz signals has raised significant attention due to its non-invasive, non-destructive, non-ionizing, material-classification, and ultrafast-frame-rate nature for object exploration and inspection. However, the material and geometric information of the tested objects is inherently embedded in the highly distorted THz time-domain signals, leading to substantial computational complexity and the necessity for intricate multi-physics models to extract the desired information. To address this challenge, we present a THz multi-dimensional tomographic framework and multi-scale spatio-spectral fusion Unet (MS3-Unet), capable of fusing and collaborating the THz signals across diverse signal domains. MS3-Unet employs multi-scale branches to extract spatio-spectral features, which are subsequently processed through element-wise adaptive filters and fused to achieve high-quality THz image restoration. Evaluated by geometry-variant objects, MS3-Unet outperforms other peer methods in PSNR and SSIM. In addition to the superior performance, the proposed framework additionally provides high scalable, adjustable, and accessible interface to collaborate with different user-defined models or methods. © 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Adaptive filters

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