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2008 International Conference on information and Knowledge Engineering, IKE 2008

作者： Sharawi, Marwa S. Sammany, Mohammed El-Beltagy, Mohammed Saroit, Imane Faculty of Informatics and Computer Science British University in Egypt Cairo Egypt Department of Applied Mathematics and Programming Aleppo University Aleppo Syria Department of Decision Support System Faculty of Computers and Information Cairo University Cairo Egypt Department of Information Technology Faculty of Computers and Information Cairo University Cairo Egypt

ISBN: (纸本)1601320752

Network Intrusion Detection Systems (NIDS) require the ability to generalize from previously observed attacks to detect even new or slight variation records of known attacks. As an intrusion detection system can be regarded as classification problem, we use Artificial Neural networks for detection. Using a benchmark study and set from the KDD (Knowledge Data Discovery and Data Mining) competition designed by DARPA and Multi-layered perceptron neural network, this Paper will aim to solve a multi class problem using MLP in to distinguish the attack records from normal ones, and also identify the attack type. In addition, it shows how to use Tikhonov regularization parameter to optimize the optimal network architecture in order to increase the system performance. The results show that the designed system is capable of classifying records with 98.34% accuracy with two hidden layers of neuron. Finally, the performance of the benchmark study is compared with our results.

关键词： Intrusion detection

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Notice of Violation of IEEE Publication Principles: The use of Cryptography in Network Security

Notice of Violation of IEEE Publication Principles: The use ...

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International Conference on Application of information and Communication Technologies (AICT)

作者： Zafar Jafarov “Information Technology and Programming” department Azerbaijan Technical University Baku Azerbaijan

Notice of Violation of IEEE Publication Principles "The Use of Cryptography in Network Security" by Zafar Jafarov in the Proceedings of the 9th International Conference on Application of information and Communication Technologies (AICT), October 2015 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles. This paper is a duplication of the original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article: "Network Security Using Cryptographic Techniques" by Sumedha Kaushik, Ankur Singhal in the International Journal of Advanced Research in Computer Science and Software Engineering, Vol 2, Issue 12, December 2012 Network Security is the most vital component in information security because it is responsible for securing all information passed through networked computers. Network Security refers to all hardware and software functions, characteristics, features, operational procedures, accountability, measures, access control, and administrative and management policy required to provide an acceptable level of protection for Hardware and Software, and information in a network. Only one particular element underlies many of the security mechanisms in use: Cryptographic techniques; hence our focus is on this area Cryptography. Cryptography is an emerging technology, which is important for network security. Research on cryptography is still in its developing stages and a considerable research effort is still required for secured communication.

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Qualitative Properties of Solutions of a Doubly Nonlinear Reaction-Diffusion System with a Source

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Journal of Applied Mathematics and Physics 2015年第9期3卷 1090-1099页

作者： Mersaid Aripov Shakhlo A. Sadullaeva Department of Informatics and Applied Programming National University of Uzbekistan Tashkent Uzbekistan Department of Multimedia Technology Tashkent University of Information Technology Tashkent Uzbekistan

In this paper, we study properties of solutions to doubly nonlinear reaction-diffusion systems with variable density and source. We demonstrate the possibilities of the self-similar approach to studying the qualitative properties of solutions of such reaction-diffusion systems. We also study the finite speed of propagation (FSP) properties of solutions, an asymptotic behavior of the compactly supported solutions and free boundary asymptotic solutions in quick diffusive and critical cases.

关键词： Double Nonlinear Reaction-Diffusion Equation Self-Similar Solution Asymptotics

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Classification Algorithms with a Complex Structure in Pattern Recognition 25

Classification Algorithms with a Complex Structure in Patter...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Nishanov, Akram Kh. Allamov, Oybek Rakhmanov, Askar T. Yusupova, Janar Ruzibaev, Ortik B. Department of Systematic and Practical Programming Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of Software Engineering Urgench Branch of Tashkent University of Information Technology named after Muhammad al Khwarizmi Urgench Uzbekistan Department of Systematic and Practical Programming Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Faculty of Software Engineering Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9798350389234

The article considers in the intellectual processing of information, moving from a large unit of measurement to a smaller, more important unit of measurement, selecting sets of informative symbols and classifying symbols, developing modern recognition systems that help specialists in the field, as well as evaluating the states of objects to be classified, developing a classification algorithm for multi-class cases of educational samples. The development of a multi-class algorithm for symbol classification serves to develop the theory of symbol recognition. It deals with the construction of a decision rule construction algorithm. Its main purpose is to determine which of the given classes the recognized object belongs to. The complexity or simplicity of the proposed algorithm depends on the number of classes participating in the study sample. If the number of classes is two, then the formulation of decision rules is simple. That is why the classification algorithms proposed by most authors are solved for cases where the number of classes is three or more, the decisive rule in the matter of classification of objects is solved by making two classes. The construction of a multi-class decision rule for classification, which takes into account all classes at the same time, is a complex and urgent issue. In the article, in the classification of objects, a multi-level complex structured decision rule was developed based on special inequalities, and two-, three- and multi-class classification algorithms were developed. © 2024 IEEE.

关键词： Consensus algorithm

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Al-Biruni Earth Radius Optimization for COVID-19 Forecasting

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Computer Systems Science & Engineering 2023年第7期46卷 883-896页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Tatiana Makarovskikh Amal H.Alharbi Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of System Programming South Ural State University454080ChelyabinskRussia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WHO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second version of the previously known severe acute respiratory syndrome(SARS)Coronavirus and identified in short as(SARSCoV-2).There have been regular restrictions to avoid the infection spread in all countries,including Saudi *** prediction of new cases of infections is crucial for authorities to get ready for early handling of the virus ***:Analysis and forecasting of epidemic patterns in new SARSCoV-2 positive patients are presented in this research using metaheuristic optimization and long short-term memory(LSTM).The optimization method employed for optimizing the parameters of LSTM is Al-Biruni Earth Radius(BER)***:To evaluate the effectiveness of the proposed methodology,a dataset is collected based on the recorded cases in Saudi Arabia between March 7^(th),2020 and July 13^(th),*** addition,six regression models were included in the conducted experiments to show the effectiveness and superiority of the proposed *** achieved results show that the proposed approach could reduce the mean square error(MSE),mean absolute error(MAE),and R^(2)by 5.92%,3.66%,and 39.44%,respectively,when compared with the six base *** the other hand,a statistical analysis is performed to measure the significance of the proposed ***:The achieved results confirm the effectiveness,superiority,and significance of the proposed approach in predicting the infection cases of COVID-19.

关键词： COVID-19 prediction meta-heuristic optimization LSTM Al-Biruni earth radius algorithm

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Design Reusability and Adaptability for Concurrent Software

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AASRI Procedia 2013年 5卷 133-139页

作者： Paniti Netinant Information Technology Department Bangkok University Bangkok Thailand Concurrent Programming Research Group Illinois Institute of Technology Chicago IL USA

Developing reusable and adaptable concurrent software are very difficult. Reusability and adaptability in concurrent software become minimal. These collaborations not only perimeter reusability, but also make modification invasive changes to meet new requirements in the design of the concurrent software. The concurrent system has to reengineer, in order to meet the future requirements. A misunderstanding, that a concurrent object-oriented programming generally endorses reusability and adaptability, as none of these problems is imposed. Software developers have to specifically deliberate software making reusability and adaptability. We present a concurrent aspect framework which better supporting reusability and adaptability. In the framework, functional components and system assets are relatively separated. This technique makes concurrent software developing better reusability and adaptability. A framework enables manageable reusability and adaptability for building of concurrent software. Our research focuses on decomposition of contact in concurrent software development and our goal is to demonstrate a better model of concurrent software design.

关键词： Aspect Orientation Adaptability Reusability Framework Concurrent Software

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Hybrid Dipper Throated and Grey Wolf Optimization for Feature Selection Applied to Life Benchmark Datasets

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Computers, Materials & Continua 2023年第2期74卷 4531-4545页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Faten Khalid Karim Mostafa Abotaleb Abdelhameed Ibrahim Abdelaziz A.Abdelhamid D.L.Elsheweikh Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of System Programming South Ural State UniversityChelyabinsk454080Russia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Specific EducationMansoura UniversityEgypt

Selecting the most relevant subset of features from a dataset is a vital step in data mining and machine *** feature in a dataset has 2n possible subsets,making it challenging to select the optimum collection of features using typical *** a result,a new metaheuristicsbased feature selection method based on the dipper-throated and grey-wolf optimization(DTO-GW)algorithms has been developed in this *** can result when the selection of features is subject to metaheuristics,which can lead to a wide range of ***,we adopted hybrid optimization in our method of optimizing,which allowed us to better balance exploration and harvesting chores more *** propose utilizing the binary DTO-GW search approach we previously devised for selecting the optimal subset of *** the proposed method,the number of features selected is minimized,while classification accuracy is *** test the proposed method’s performance against eleven other state-of-theart approaches,eight datasets from the UCI repository were used,such as binary grey wolf search(bGWO),binary hybrid grey wolf,and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hysteresis optimization(bHy),and binary hysteresis optimization(bHWO).The suggested method is superior 4532 CMC,2023,vol.74,no.2 and successful in handling the problem of feature selection,according to the results of the experiments.

关键词： Metaheuristics dipper throated optimization grey wolf optimization binary optimizer feature selection

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Design Reusability and Adaptability for Concurrent Software

Design Reusability and Adaptability for Concurrent Software

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The 2013 AASRI Conference on Parallel and Distributed Computing and Systems(DCS 2013)

作者： Paniti Netinant Information Technology Department Bangkok University Concurrent Programming Research Group Illinois Institute of Technology

Developing reusable and adaptable concurrent software are very *** and adaptability in concurrent software become *** collaborations not only perimeter reusability,but also make modification invasive changes to meet new requirements in the design of the concurrent *** concurrent system has to reengineer,in order to meet the future requirements.A misunderstanding,that a concurrent object-oriented programming generally endorses reusability and adaptability,as none of these problems is *** developers have to specifically deliberate software making reusability and *** present a concurrent aspect framework which better supporting reusability and *** the framework,functional components and system assets are relatively *** technique makes concurrent software developing better reusability and adaptability.A framework enables manageable reusability and adaptability for building of concurrent *** research focuses on decomposition of contact in concurrent software development and our goal is to demonstrate a better model of concurrent software design.

关键词： Aspect Orientation Adaptability Reusability Framework Concurrent Software

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A proposal of Ontology-based health care information extraction system: VnHIES

A proposal of Ontology-based health care information extract...

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2007 IEEE International Conference on Research, Innovation and Vision for the Future, RIVF 2007

作者： Dung, Tran Quoc Kameyama, Wataru Art and Multimedia Science Department Graduate School of Information and Tele-communication Studies Waseda University Database and Programming Department Institute of Information Technology Viet Nam Art and Multimedia Science Faculty Global Information and Tele-Communication Studies Graduate School Waseda University Japan Art and Multimedia Science GITS Waseda University Japan

ISBN: (纸本)1424406943

This paper presents an Ontology-based health care information extraction system - VnHIES. In the system, we develop and use two effective algorithms called "Semantic Elements Extracting Algorithm" and "New Semantic Elements Learning Algorithm" for health care semantic words extraction and ontology enhancement. The former algorithm will extract Concepts (Cs), Descriptions of concepts (Ds), Pairs of Concept and Description(C-D) and Names of diseases (Ns) in health care information domain from web pages. Those extracted semantic elements are used by latter algorithm that will render suggestions in which might contain new semantic elements for later use by domain users to enrich ontology. After extracting semantic elements, a "Document Weighting Algorithm" is applied to get summary information of document with respect to all extracted semantic words and then to be stored in knowledge base which contains ontology and database to be used later in other applications. Our experiment results show that the approach is very optimistic with high accuracy in semantic extracting and efficiency in ontology upgrade. VnHIES can be used in many health care information management systems such as medical document classification, health care information retrieval system. VnHIES is implemented in Vietnamese language. © 2007 IEEE.

关键词： information systems

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Social Engineering Attacks Detection Approach 13

Social Engineering Attacks Detection Approach

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13th International Conference on Dependable Systems, Services and Technologies, DESSERT 2023

作者： Lysenko, Sergii Vorobiov, Volodymyr Bokhonko, Oleksandr Gaj, Piotr Savenko, Oleg Woloszyn, Jacek Khmelnitsky National University Department of Computer Engineering and Information Systems Khmelnitsky Ukraine Silesian University of Technology Gliwice Poland Khmelnitsky National University Department of Computer Engineering and System Programming Khmelnitsky Ukraine Kazimierz Pulaski University of Technology and Humanities in Radom Department of Informatics and Teleinformatics Radom Poland

ISBN: (纸本)9798350396119

The paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits frequently capitalize on human psychology, trust, and a lack of vigilance to attain unauthorized entry to networks, systems, or data. In contrast to traditional social engineering tactics that center on psychological manipulation, technical social engineering attacks employ technological means and strategies to manipulate and beguile individuals. The paper presents an attempt to detect social engineering attacks. The approach utilized four machine learning algorithms (decision tree, random forest, K-nearest neighbor, and extreme gradient boosting). The analysis is centered on data collected from network hosts, which may serve as indicators of a potential social engineering attack. The empirical results demonstrated high detection accuracy. © 2023 IEEE.

关键词： Cybersecurity

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