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Smart Energy Management System Using Machine Learning

computers, Materials & Continua 2024年第1期78卷 959-973页

作者： Ali Sheraz Akram Sagheer Abbas Muhammad Adnan Khan Atifa Athar Taher M.Ghazal Hussam Al Hamadi School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnamGyeonggido13120Korea Department of Computer Science COMSATS University IslamabadLahore CampusLahore54000Pakistan School of Information Technology Skyline University CollegeSharjah1797United Arab Emirates Network and Communication Technology Lab Center for Cyber SecurityFaculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia College of Engineering and IT University of DubaiDubaiUnited Arab Emirates

Energy management is an inspiring domain in developing of renewable energy ***,the growth of decentralized energy production is revealing an increased complexity for power grid managers,inferring more quality and reliability to regulate electricity flows and less imbalance between electricity production and *** major objective of an energy management system is to achieve optimum energy procurement and utilization throughout the organization,minimize energy costs without affecting production,and minimize environmental *** energy management is an essential and complex subject because of the excessive consumption in residential buildings,which necessitates energy optimization and increased user *** address the issue of energy management,many researchers have developed various frameworks;while the objective of each framework was to sustain a balance between user comfort and energy consumption,this problem hasn’t been fully solved because of how difficult it is to solve *** inclusive and Intelligent Energy Management System(IEMS)aims to provide overall energy efficiency regarding increased power generation,increase flexibility,increase renewable generation systems,improve energy consumption,reduce carbon dioxide emissions,improve stability,and reduce energy *** Learning(ML)is an emerging approach that may be beneficial to predict energy efficiency in a better way with the assistance of the Internet of Energy(IoE)*** IoE network is playing a vital role in the energy sector for collecting effective data and usage,resulting in smart resource *** this research work,an IEMS is proposed for Smart Cities(SC)using the ML technique to better resolve the energy management *** proposed system minimized the energy consumption with its intelligent nature and provided better outcomes than the previous approaches in terms of 92.11% accuracy,and 7.89% miss-rate.

关键词： Intelligent energy management system smart cities machine learning

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An Efficient Classifier: Kernel SVM-LDA 1

An Efficient Classifier: Kernel SVM-LDA

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1st International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2022

作者： Tehrani, Fahimeh Jamshidian Nasihatkon, Behrooz Al-Qawasmi, Khaled Al-Mousa, Mohammad Rasmi Boostani, Reza School of Computer Engineering Khajeh Nasir University of Technology Tehran Iran Zarqa University Faculty of Information Technology Department of Cyber Security Zarqa Jordan Shiraz University Shiraz Faculty of Electrical and Computer Engineering Iran

ISBN: (纸本)9798350332742

This study aims at designing an efficient combinatorial classifier, which fuses linear discriminant analysis (LDA) and kernel support vector machine (SVM) classifiers. The proposed method is called kernel SVM-LDA which benefits from global property of LDA, simultaneous with localized capability of SVM along with mapping ability of RBF kernel to project input data into a more separable high dimensional space. To assess the proposed scheme, Kernel SVM-LDA was applied to some standard datasets derived from UCI database and then compared to standard LDA and kernel SVM classifiers. Kernel SVM-LDA was also employed in cue-based brain computer interface to classify the left and right imagery movements. The results indicate that the introduced method is more superior to that of LDA and kernel SVM because it surpasses the counterparts in terms of robustness, complexity and performance. © 2022 IEEE.

关键词： Support vector machines

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Cybersecurity Threats in the Era of AI: Detection of Phishing Domains Through Classification Rules 2

Cybersecurity Threats in the Era of AI: Detection of Phishin...

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2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Aljaidi, Mohammad Alsarhan, Ayoub Al-Fraihat, Dimah Al-Arjan, Ahmed Igried, Bashar El-Salhi, Subhieh M. Khalid, Muhammad Al-Na'amneh, Qais Zarqa University Faculty of Information Technology Department of Computer Science Zarqa13110 Jordan The Hashemite University Department of Information Technology Jordan Isra University Faculty of Information Technology Department of Software Engineering Amman11622 Jordan The Hashemite University Faculty of Prince AL-Hussein Bin Abdullah Ii of Information Technology Department of Information Technology Jordan The Hashemite University Department of Computer Science and Applications Zarqa Jordan The Hashemite University P. O Box 330127 Zarqa13133 Jordan University of Hull Department of Computer Sciences and Technology Kingston upon Hull United Kingdom Applied Science Private University Dep. of Cyber Security Amman Jordan

ISBN: (纸本)9798350373363

Phishing is a cyber threat where attackers create deceptive websites or emails to exploit individuals for fraudulent purposes such as providing sensitive information like usernames, passwords, or financial details. Hence, detecting phishing emails is of paramount importance to protect sensitive information, preventing financial losses, protecting against identity theft, and maintaining trust. This study employs machine learning techniques to classify and categorize websites that are used for phishing attacks. To achieve this, we proposed a classification model for the detection of phishing domains based on classification rules. These rules were formulated based on analyzing and distributing them into three classifiers: domain name features, search engine opinion (SEO) information of the domain, and security scans by security vendors. A total of eleven classification rules were formulated which were distributed as follows: six rules for the first classifier, four rules for the second classifier, and one rule for the third classifier. Each classifier feeds its results to the main classifier, which then evaluates the received results based on its rules. Domain names from 222 confirmed phishing URLs were used to test the suggested model. The model demonstrated exceptional performance, achieving an impressive accuracy rate of 99.1% during testing. © 2023 IEEE.

关键词： Websites

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Efficient Segmentation Approach for Different Medical Image Modalities

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computers, Materials & Continua 2022年第11期73卷 3119-3135页

作者： Walid El-Shafai Amira A.Mahmoud El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

This paper presents a study of the segmentation of medical *** paper provides a solid introduction to image enhancement along with image segmentation *** the first step,the morphological operations are employed to ensure image detail protection and *** objective of using morphological operations is to remove the defects in the texture of the ***,the Fuzzy C-Means(FCM)clustering algorithm is used to modify membership function based only on the spatial neighbors instead of the distance between pixels within local spatial neighbors and cluster *** proposed technique is very simple to implement and significantly fast since it is not necessary to compute the distance between the neighboring pixels and the cluster *** is also efficient when dealing with noisy images because of its ability to efficiently improve the membership partition *** results are performed on different medical image ***(Us),X-ray(Mammogram),Computed Tomography(CT),Positron Emission Tomography(PET),and Magnetic Resonance(MR)images are the main medical image modalities used in this *** obtained results illustrate that the proposed technique can achieve good results with a short time and efficient image *** results on different image modalities show that the proposed technique can achieve segmentation accuracies of 98.83%,99.71%,99.83%,99.85%,and 99.74%for Us,Mammogram,CT,PET,and MRI images,respectively.

关键词： Image segmentation ultrasonic mammogram CT PET MRI morphological operations FCM active contours

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Hybrid Segmentation Approach for Different Medical Image Modalities

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computers, Materials & Continua 2022年第11期73卷 3454-3471页

作者： Walid El-Shafai Amira A.Mahmoud El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

The segmentation process requires separating the image region into sub-regions of similar *** sub-region has a group of pixels having the same characteristics,such as texture or *** paper suggests an efficient hybrid segmentation approach for different medical image modalities based on particle swarm optimization(PSO)and improved fast fuzzy C-means clustering(IFFCM)*** extensive comparative study on different medical images is presented between the proposed approach and other different previous segmentation *** existing medical image segmentation techniques incorporate clustering,thresholding,graph-based,edge-based,active contour,region-based,and watershed *** paper extensively analyzes and summarizes the comparative investigation of these ***,a prediction of the improvement involves the combination of these techniques is *** obtained results demonstrate that the proposed hybrid medical image segmentation approach provides superior outcomes in terms of the examined evaluation metrics compared to the preceding segmentation techniques.

关键词： Image segmentation ultrasonic images X-ray images CT images PET images MR images fuzzy c-mean morphological operations active contour

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A Hybrid security Framework for Medical Image Communication

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computers, Materials & Continua 2022年第11期73卷 2713-2730页

作者： Walid El-Shafai Hayam A.Abd El-Hameed Ashraf A.M.Khalaf Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Electrical Communications Engineering Department Faculty of EngineeringMinia UniversityMinia61111Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

Authentication of the digital image has much attention for the digital *** image authentication can be verified with image watermarking and image encryption *** schemes are widely used to protect images against forgery attacks,and they are useful for protecting copyright and rightful *** on the desirable applications,several image encryption and watermarking schemes have been proposed to moderate this *** framework presents a new scheme that combines a Walsh Hadamard Transform(WHT)-based image watermarking scheme with an image encryption scheme based on Double Random Phase Encoding(DRPE).First,on the sender side,the secret medical image is encrypted using *** the encrypted image is watermarking based on *** combination between watermarking and encryption increases the security and robustness of transmitting an *** performance evaluation of the proposed scheme is obtained by testing Structural Similarity Index(SSIM),Peak Signal-to-Noise Ratio(PSNR),Normalized cross-correlation(NC),and Feature Similarity Index(FSIM).

关键词： Walsh hadamard transform watermarking encryption double random phase encoding structural similarity index

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Comparative Analysis of Data Dynamics Based on Wavelet Coherence Using Higher-Order Moments 2

Comparative Analysis of Data Dynamics Based on Wavelet Coher...

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2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Al-Sharo, Yasser Abu-Jassar, Amer Vasiurenko, Oleg Lyashenko, Vyacheslav Ajloun National University Faculty of Information Technology Department of Cyber Security Ajloun Jordan Ajloun National University Faculty of Information Technology Department of Computer Science Ajloun Jordan Kyiv University of Intellectual Property and Law Department of Cybersecurity It and Economics Kyiv Ukraine Kharkiv National University of Radio Electronics Department of Media Systems and Technology Kharkiv Ukraine

ISBN: (纸本)9798350373363

The article addresses the challenges of analyzing data represented as time series, depicting the evolution of a specific process, phenomenon, or object over time. Special emphasis is placed on conducting a comparative analysis of the dynamics among different data sets;so, to achieve this, a method for estimating wavelet coherence is employed. The approach includes transforming the original data through a sliding sampling window using higher-order moments to capture the memory effect. This methodology enables the assessment of dynamics in extensive data sets, thereby enhancing the efficiency of processing and analysis. The article presents results based on real data, providing an additional evaluation of their mutual dynamics. The findings affirm the reliability and effectiveness of such an analysis. © 2023 IEEE.

关键词： Dynamics

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Defensive Auto-Updatable and Adaptable Bot Recommender System (DAABRS): A New Architecture Approach in Cloud Computing Systems 6

Defensive Auto-Updatable and Adaptable Bot Recommender Syste...

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6th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2024

作者： Khwaldeh, Sufian Mohit, Y. Khushwant, S. Department of Network and Information Security College of lnformation Technology University of Fujairah 1207 United Arab Emirates Department of Information Technology Faculty of Information Technology and Systems The University of Jordan Aqaba77110 Jordan Department of Mathematics University Institute of Sciences Chandigarh University Punjab Mohali140413 India Department of Computer Science & Engineering University Institute of Engineering and Technology M. D. University Rohtak124001 India

ISBN: (纸本)9798350394634

Cloud server data security makes extensive use of data centers and instantly accessible edge systems for possible transactions involving sizable and confidential data. These Edge Systems are chosen for rental based on their usefulness in situations where new privacy and security difficulties must be overcome. The use of Edge Systems is subject to dynamic mobility, which increases the danger of attacking threats. With this suggested approach, the Defensive Auto-updatable and Adaptable Bot Recommender approach (DAABRS) is used by the Cloud Center to identify the safeguarded Edge System. Cloud Data Centers with Edge Systems contain a variety of users and environments, making it simple for attackers to enter anonymously and compromise Edge System privacy. The most effective security measure against increasing risks and assaults for Edge Systems that rent more cloud storage is to use Stealth Mode Bots inside of data segments. In addition to anticipating and averting data breaches in server partitioning, tenant systems, edge systems, and containers by integrating stealth mode bots into each. Suggested use cases: Tenants, Edge Systems, or Containers for effective security-enhanced Stealth Mode Bots that are activated when a particular data segment is unplugged. Updatable and adaptive bots are used in the suggested strategy to counter Edge strategy assaults. Additionally, it uses Stealth Mode Bots to stop heavily attacked Data Containers, and machine learning will be used to update specifications to identify and prevent further assaults. © 2024 IEEE.

关键词： Containers

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Teaching pentesting to social sciences students using experiential learning techniques to improve attitudes towards possible cybersecurity careers 22

Teaching pentesting to social sciences students using experi...

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22nd European Conference on Cyber Warfare and security, ECCWS 2023

作者： Melnikovas, Aleksandras Lugo, Ricardo G. Maennel, Kaie Brilingaite, Agne Sutterlin, Stefan Juozapavicius, Ausrius General Jonas Zemaitis Military Academy of Lithuania Lithuania Faculty of Health Welfare and Organisation Ostfold University College Norway School of Information Technology Tallinn University of Technology Tallinn Estonia Institute of Computer Science Vilnius University Vilnius Lithuania School of Computer and Mathematical Sciences The University of Adelaide Adelaide Australia Department of Information Security and Communication Technology Norwegian University of Science and Technology Norway Faculty of Computer Science Albstadt-Sigmaringen University Sigmaringen Germany

ISBN: (纸本)9781914587702

Labor market analysis shows that there is a significant shortage of experienced cybersecurity professionals, and this trend is expected to continue in the future. In addition, young people who are reluctant to choose STEM subjects in school typically do not see cybersecurity as a part of their future because they believe it demands exclusive technical knowledge that is beyond their reach. We aimed to change this perception among students of the social sciences, assuming that by providing social science students with the basics of cybersecurity, it would be possible to raise their awareness and encourage them to consider this field as a potential career option. Our team has designed a concise technical course based on Kolb's model that employs experiential learning to provide students with a basic knowledge of ethical intrusion (penetration testing). During the 32-hour subject, cadet officers with no prior IT education experienced all the steps of hacking both into a remotely accessible and physically accessible computer, including initial reconnaissance, vulnerability scanning, exploitation, and privilege escalation. A hands-on practical task of breaking into a highly vulnerable remote computer allowed for the evaluation of knowledge and skills as well as the reinforcement of learning experiences. In order to assess how the students' perceptions of the cybersecurity profession have changed based on the theory of planned behavior, they were asked to provide feedback immediately after the course and one year later. The results indicate that the short, technically challenging, but practical course based on experiential learning had a significant and positive effect on participants' attitudes: They were substantially more likely to consider cybersecurity as a future career, and some of them began participating in other cybersecurity courses or activities. It is reasonable to assume, therefore, that providing similar technical courses to social science students will enco

关键词： Students

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Single Qubit Quantum Logistic-Sine XYZ-Rotation Maps:An Ultra-Wide Range Dynamics for Image Encryption

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computers, Materials & Continua 2025年第5期83卷 2161-2188页

作者： De Rosal Ignatius Moses Setiadi T.Sutojo Supriadi Rustad Muhamad Akrom Sudipta Kr Ghosal Minh T.Nguyen Arnold Adimabua Ojugo Research Center for Quantum Computing and Materials Informatics Faculty of Computer ScienceDian Nuswantoro UniversitySemarang50131Indonesia Department of Cyber Forensics and Information Security Behala Government Polytechnic756Upendra Nath Banerjee RoadParnasreeBehalaKolkata700060India Thai Nguyen University of Technology Thai Nguyen UniversityThai Nguyen240000Vietnam Department of Computer Science Federal University of Petroleum ResourcesEffurun330102Nigeria

Data security has become a growing priority due to the increasing frequency of cyber-attacks,necessitating the development of more advanced encryption *** paper introduces Single Qubit Quantum Logistic-Sine XYZ-Rotation Maps(SQQLSR),a quantum-based chaos map designed to generate one-dimensional chaotic sequences with an ultra-wide parameter *** proposed model leverages quantum superposition using Hadamard gates and quantum rotations along the X,Y,and Z axes to enhance *** numerical experiments validate the effectiveness of *** proposed method achieves a maximum Lyapunov exponent(LE)of≈55.265,surpassing traditional chaotic maps in *** bifurcation analysis confirms a uniform chaotic distribution,eliminating periodic windows and ensuring higher *** system also generates an expanded key space exceeding 10^(40),enhancing security against brute-force ***,SQQLSR is applied to image encryption using a simple three-layer encryption scheme combining permutation and substitution *** approach is intentionally designed to highlight the impact of SQQLSR-generated chaotic sequences rather than relying on a complex encryption *** method achieves an average entropy of 7.9994,NPCR above 99.6%,and UACI within 32.8%–33.8%,confirming its strong randomness and sensitivity to minor *** robustness tests against noise,cropping,and JPEG compression demonstrate its resistance to statistical and differential ***,the decryption process ensures perfect image reconstruction with an infinite PSNR value,proving the algorithm’s *** results highlight SQQLSR’s potential as a lightweight yet highly secure encryption mechanism suitable for quantum cryptography and secure communications.

关键词： Single qubit quantumchaotic quantumchaotic map quantumimage encryption quantumlogistic map quantum sine map

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