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Genetic Optimization Techniques for Enhancing Web Attacks Classification in Machine Learning

Genetic Optimization Techniques for Enhancing Web Attacks Cl...

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2023 IEEE International Conference on dep.ndable, Autonomic and Secure Computing, 2023 International Conference on Pervasive Intelligence and Computing, 2023 International Conference on Cloud and Big Data Computing, 2023 International Conference on Cyber science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Jaradat, Ameera S. Nasayreh, Ahmad Al-Na'amneh, Qais Gharaibeh, Hasan Al Mamlook, Rabia Emhamed Yarmouk University Dep. of Computer Science Irbid Jordan Yarmouk University Dep. of Computer Science Irbid211633 Jordan Applied Science Private University Dep. of Cyber Security and Cloud Computing Amman Jordan Trine University Dep. of Business Administration IN United States University Zawia Department of Industrial Engineering Tripoli Libya

ISBN: (纸本)9798350304602

Web-based applications are now the preferred approach for delivering a variety of services via the Internet. As a result of the globalization of commerce, web applications have been growing quickly and becoming increasingly complicated. Such applications have a significant security vulnerability in the online environment since they were developed with little experience and without testing or validation. Numerous attackers use this security vulnerability to take control of the program, modify the data, and steal the most crucial information. They may also access all internal, unauthorized items. This work presents a hybrid model that classifies website attacks as benign through the integration of four machine learning algorithms: gradient boost (GB), multilayer perceptron (MLP), logistic regression (LR) and K nearest neighbor (KNN). The work dep.oyed Tree-based Pipeline Optimization Tool (TPOT) that utilizes the Genetic algorithm (GA) to extract the optimal parameter and consequently enhance the model performance. The model underwent evaluation utilizing a data set from the Canadian Institute 2023 that contains various types of attacks. Among these algorithms, GB achieved the best accuracy scores of 95%, 94% and 95% for accuracy, recall and F1-score, respectively. © 2023 IEEE.

关键词： Genetic algorithms

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Biological age estimation from ECG using Artificial Intelligence approaches 2

Biological age estimation from ECG using Artificial Intellig...

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2nd Jordanian International Biomedical engineering Conference, JIBEC 2024

作者： Sleiman, Jana Daher, Mohamad Khalil, Mohamad Diab, Ahmad Kassem, Abdallah Lebanese University Computer and Communications Engineering Tripoli Lebanon Faculty of Science Faculty of Applied Sciences & Technology Dep. of Computer Science Dep. of Computer Science & Information Technology Tripoli Lebanon Lebanese University Electrical Engineering Tripoli Lebanon Lebanese International University Biomedical Engineering Beirut Lebanon Notre Dame University Faculty Of Engineering ECCE Dept. Zouk Mosbeh Lebanon

ISBN: (纸本)9798331539542

This paper explores the application of Artificial Intelligence (AI) techniques in healthcare, specifically focusing on electrocardiogram (ECG) data analysis and biological age estimation. The study begins with an overview of ECG as a diagnostic tool and discusses the integration of Deep Learning (DL) models, particularly Convolutional Neural Networks (CNNs), in healthcare for various applications. Previous studies reviewed in this context consistently identify CNNs as the superior model for ECG analysis and prediction tasks. The primary research investigates the use of Machine Learning (ML) algorithms to estimate biological age from ECG data, employing metrics such as Mean Absolute Error (MAE) and variance to evaluate model performance. Subsequently, DL models are implemented and compared, demonstrating superior accuracy in estimating the biological age of new patients. While both ML and DL approaches were initially explored, this paper primarily focuses on deep learning methodologies due to their demonstrated superiority in healthcare applications. The findings highlight the efficacy of deep learning over traditional ML methods, underscoring its potential for enhancing diagnostic accuracy and personalized patient care. For instance, the most accurate deep learning model, the Convolutional Neural Network (CNN), achieved a Mean Absolute Error (MAE) of 1.49 and an R2 score of 0.53, whereas the best-performing traditional ML model, Random Forest, achieved an MAE of 1.54 and an R2 score of 0.55. These results clearly indicate the advantage of deep learning models in capturing complex patterns in ECG data, leading to more precise and reliable estimations of biological age. © 2024 IEEE.

关键词： Convolutional neural networks

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Evaluating the Impact of Injected Mobility Data on Measuring Data Coverage in CrowdSensing Scenarios

Evaluating the Impact of Injected Mobility Data on Measuring...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Kocian, Alexander Girolami, Michele Capoccia, Stefano Foschini, Luca Chessa, Stefano University of Bologna Department of Computer Science and Engineering Bologna Italy ISTI-CNR Italian National Council of Research Pisa Italy University of Pisa Dep. of Computer Science Italy

ISBN: (纸本)9798350351255

A major weakness of Mobile CrowdSensing Platforms (MCS) is the willingness of users to participate, as this implies disclosing their private data (for example, concerning mobility) to the MCS platform. In the effort to enforce data privacy in the creation of mobility coverage maps using an MCS platform, recent work proposes the use of a spatially distributed approach that, however, is vulnerable to data injection attacks. In this contribution, we define and implement a progressive attacker model following a statistical approach. We propose a novel mitigation strategy based on unsupervised anomaly detection. Accessing the coverage performance with real-world mobility data indicates that the mean value of the attacker's profile determines the probability of being revealed. In particular, we are able to identify the attacker and filter out the data injected by the attackers with high precision. © 2024 IEEE.

关键词： Differential privacy

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Performance Analysis of Intelligent Reflecting Surfaces for 5G/6G-Enabled Future Smart Industries with a Focus on Millimeter-Wave Band Communications 59

Performance Analysis of Intelligent Reflecting Surfaces for ...

引用

2024 Annual IEEE International Conference on Communications Workshops, ICC Workshops 2024

作者： Khan, Muhammad Farhan Raza, Ali Iqbal, Adeel Rashid, Adnan Jamshed, Muhammad Ali Pesch, Dirk School of Computer Science and Information Technology University College Cork Cork Ireland Comsats University Islamabad Dep. of Electrical and Computer Engineering Pakistan Yeungnam University Dep. of Info. & Com. Engineering Gyeongsan-si38541 Korea Republic of Politecnico di Bari Dep. of Electrical & Information Engineering Bari Italy James Watt School of Engineering University of Glasgow Glasgow United Kingdom

ISBN: (纸本)9798350304053

Industry 4.0's emergence necessitates reliable communication systems. Millimeter-wave (mmWave) communication is a promising solution, but challenges like limited coverage and atmospheric absorption persist. The Intelligent Reflecting Surfaces (IRS) offers transformative potential by dynamically manipulating wave propagation to improve millimeter-wave (mmWave) communication. This research investigates the impact of the distance of Industrial User Equipment (iUE) from the IRS and Base Station (BS), and the height of the IRS from the ground, along with the impact of sum throughput by increasing the number of IRS elements. The IRS-assisted system exhibits enhanced performance within the mmWave frequency band compared to the sub-6 GHz band. The observed achievable rate gains, exceeding 200% on average, underscore the significant performance enhancement enabled by IRS dep.oyments. Moreover, increasing the number of IRS elements significantly enhances the overall throughput. The decrease in required transmit power with an increasing number of Intelligent Reflecting Surfaces IRS elements can be attributed to the enhanced ability of IRS to efficiently reflect and manipulate electromagnetic waves. As more IRS elements are dep.oyed, they collectively contribute to optimizing signal propagation, allowing for better control and redirection of the transmitted signals. This phenomenon enables the system to achieve the desired communication objectives with less overall transmit power. Additionally, the attainable capacity of the examined IRS-assisted wireless communication system exhibits growth alongside an increase in the elevation of the IRS installation. Results showcase the potential of IRSs to enhance coverage and communication reliability, providing valuable insights for designing efficient wireless systems in smart factories and Industry 4.0 applications. © 2024 IEEE.

关键词： 5G mobile communication systems

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Packet Too Big Detection and its Integration into QUIC 16

Packet Too Big Detection and its Integration into QUIC

引用

16th International Conference on Signal Processing and Communication System, ICSPCS 2023

作者： Völker, Timo Tuxen, Michael FH Münster University of Applied Sciences Dep. of Electrical Engineering and Computer Science Steinfurt Germany

ISBN: (纸本)9798350333510

A communication over an Internet Protocol (IP) based network fails if an endpoint sends packets that are too big to reach their destination and if the sender is unable to detect that. The node on the path that drops these packets should respond with a Packet Too Big (PTB) message. However, multiple scenarios exist in which the sender will not receive a PTB message. Even if it does, it refrains from using the information in case it suspects that a potential attacker forged the message. In particular, we are not aware of any implementation of the secure transport protocol QUIC (e.g., used by HTTP/3) that processes PTB messages. In this paper, we present a novel parameterizable PTB detection algorithm for reliable transport protocols that does not dep.nd on PTB messages. We further describe how to integrate our algorithm into QUIC, present results from an evaluation using the algorithm within a QUIC simulation model and, based on these results, suggest concrete parameter values. © 2023 IEEE.

关键词： HTTP

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Studying Risks of Hybrid Reengineering on Air-Transportation Systems Management 'A Case Study on Jordanian civil Aviation Regulatory Commission (CARC)' 24

Studying Risks of Hybrid Reengineering on Air-Transportation...

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24th International Arab Conference on Information Technology, ACIT 2023

作者： Al Refai Mohammed, N. Taani, M.K. Otoom, Ahmed Ali Samara, Ghassan Hanandeh, S.E. Khafajeh, Hayel Zarqa University Software Engineering Dep. Zarqa Jordan Applied Science Private University Cybersecurity and Cloud Computing Dep. Amman Jordan Zarqa University Department of Computer Science Zarqa Jordan Zarqa University Artificial Intelligence Dep. Zarqa Jordan

ISBN: (纸本)9798350384307

This study examines decision-making in software re-engineering within businesses, focusing on the challenges and considerations involved. Financial constraints, time, and staff efforts are critical factors in these decisions. The study identifies difficulties faced by top-level management with legacy systems, existing systems, underused systems, and packaged software due to user resistance and customer dissatisfaction. The primary goal of the study is to assess the importance of software quality factors, especially from the users' perspective, in making re-engineering decisions. It uses the ISO 9126 Model to analyze quality elements in the case study software, aiming to provide guidance for deciding whether to proceed with re-engineering. The study explores functionality, reliability, usability, efficiency, maintainability, and portability as factors influencing re-engineering decisions, based on the ISO 9126 model. To understand user interactions and program performance, the study used unstructured participant observation in the case study software, highlighting the challenges faced by top management due to user resistance. These findings were further confirmed through face-to-face interviews with software users and dep.rtment employees, offering insights into their perspectives on software quality elements. The results reveal that, despite some flaws, the system has valuable features and capabilities. Most employees express a desire to undergo re-engineering to enhance service quality, align with ISO 9126 standards, and leverage the expertise of competent staff for re-engineering activities. © 2023 IEEE.

关键词： customer dissatisfaction ISO 9126 model decision-making software quality factors software re-engineering User acceptance

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Fine-Tuning Pre-Trained Models for Automated Analysis of Ophthalmic Imaging in Diagnosing Eye Diseases 24

Fine-Tuning Pre-Trained Models for Automated Analysis of Oph...

引用

24th International Arab Conference on Information Technology, ACIT 2023

作者： Al Mamlook, Rabia Emhamed Nasayreh, Ahmad Gharaibeh, Hasan Aljaidi, Mohammad Al-Na'amneh, Qais Alzu'bi, Dalia Bzizi, Hanin Abdeltawab, Abdelrahman Trine University Dep. of Business Administration Indiana United States University Zawia Department of Industrial Engineering Tripoli Libya Yarmouk University Dep. Computer Science Irbid Jordan Zarqa University Dep. of Computer Science Zarqa Jordan Applied Science Private University Dep. of Cyber Security Amman Jordan Concordia University Dep. Information and Systems Engineering Montreal Canada Western Michigan University Dep of Biomedical Science KalamazooMI49008 United States Bani Sweif University Faculty of Pharmacy Bani Suwayf Egypt

ISBN: (纸本)9798350384307

This paper searches into the convergence of such ad-vanced techniques with architectures like DenseNet201, VGG16, InceptionResNetV2, and NasNetMobile. Our focus centers on harnessing deep learning capabilities for the precise detection of eye ailments. Preliminary findings spotlight a notable uplift in diagnostic precision. Among the tested algorithms, the Nas-NetMobile architecture emerged superior, boasting an impressive accuracy rate of 92% on the chosen dataset. Through this work, we extend a significant advancement in the realm of automated eye disease diagnosis, potentially equipping medical professionals with sharper, swifter diagnostic tools. The outcomes presented herein could play a seminal role in sculpting more sophisticated and precise diagnostic approaches within ophthalmology. © 2023 IEEE.

关键词： Deep Learning Eye Disease Fine Tuning Transfer Learning

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RF-Based Lightweight Machine Learning for Comprehensive Drone Activity Classification 2

RF-Based Lightweight Machine Learning for Comprehensive Dron...

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2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Alqodah, Mohammed A. Tahsin, Mahdia Omari, Mohammad H. Matalgah, Mustafa M. Harrison, David University of Mississippi Dep. of Electrical & Computer Engineering UniversityMS United States University of Mississippi Dept. of Computer and Information Science UniversityMS United States

ISBN: (纸本)9798331529529

The rapid rise of commercially available drones, driven by miniaturization and affordability, has introduced potential security risks alongside numerous societal benefits. While drones serve various industries, their unregulated use necessitates robust detection and classification methods. This paper proposes a novel, efficient model for classifying unwanted drone activity. We leverage statistical and time-domain features extracted from radio frequency (RF) signals and machine learning (ML) classifiers. This approach aims to not only detect drones but also distinguish their models and operational modes. Utilizing the DroneRF dataset, our feature selection strategy prioritizes informative signals in the low-band spectrum, achieving {100%} accuracy in both drone detection and drone model identification tasks. Furthermore, our hybrid model, combining time-domain and frequency-domain features, achieves an accuracy of {97.66%} in classifying different flight modes. This demonstrates the effectiveness of this comprehensive feature extraction approach for drone activity classification. © 2024 IEEE.

关键词： Drones

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MPI Impact in C+L+S Multiband Transmission Reach

MPI Impact in C+L+S Multiband Transmission Reach

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2024 Photonic Networks and Devices, NETWORKS 2024

作者： Cancela, Luís G. Pires, João O. Instituto de Telecomunicações Dep. Information Science and Technology Iscte Instituto Universitário de Lisboa Portugal Instituto de Telecomunicações Dep. Electrical and Computer Engineering Instituto Superior Técnico Portugal

Multipath interference (MPI) impact is assessed in a C+L+S multiband transmission scenario. For a typical -34 dB/span MPI, transmission reach in the L-band suffers a 20% reach penalty considering the QPSK modulation f... 详细信息

关键词： C++ (programming language)

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Maximize Leader Election Algorithm Performance in Bi-Directional Ring Networks With Both Links Down Between Two Nodes 25

Maximize Leader Election Algorithm Performance in Bi-Directi...

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Al Refai, Mohammed N. Fawareh, Hamed Aljawawdeh, Hamzeh Alshraiedeh, Fuad Sameh Al-Quraan, Mohammad Al-Odat, Hisham Ali Otoom, Ahmed Jamhawi, Zeyad M. Kanan, Mohammad Zarqa University Software Engineering Dep. Zarqa Jordan Zarqa University Zarqa Jordan Applied Science Private University Department of Cyber Security Amman Jordan Applied Science Private University Department of Computer Science Amman Jordan University of Business and Technelogy Dep. of Industry Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

The process of selecting a leader to avoid instability in distributed system network after leader failure is called Leader Election Algorithm (LEA). This process becomes more complicated when it faces intermittent or complete links disconnected. the network becomes a one-way behavior if both lines of communication between two points are disrupted and thus the network becomes very slow, especially in systems where time is a critical issue, and the process of communication between points becomes much slower if the network leader is next to the fault or close to it, so the criteria will be established to ensures that the system leader in the Bidirectional ring communication network is in a place that allows next leader to communicate with all points as quickly as possible, and this will be during the election *** research presents a solution for leader failure problem in bidirectional ring network. This research takes into account the existence of intermittent or disconnection links between nodes. It will produce three algorithms to determine a new leader in the network with maximum network performance. It uses the least probability of time steps and the number of messages needed to elect the new leader in bidirectional ring network with N communicated nodes. so that the system remains able to work and communicate with its best capacity during this problem with the number of message complexity O(N) in the worst case. The third scenario minimizes the value of proper leader ID IDCurrent/IDCurrent-idStepCount', and maximizes the value of proper leader place N - (N - nStepCount). © 2024 IEEE.

关键词： Artificial intelligence

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