• Title/Summary/Keyword: Security Area

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Medical Image Classification using Pre-trained Convolutional Neural Networks and Support Vector Machine

  • Ahmed, Ali
    • International Journal of Computer Science & Network Security
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    • v.21 no.6
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    • pp.1-6
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    • 2021
  • Recently, pre-trained convolutional neural network CNNs have been widely used and applied for medical image classification. These models can utilised in three different ways, for feature extraction, to use the architecture of the pre-trained model and to train some layers while freezing others. In this study, the ResNet18 pre-trained CNNs model is used for feature extraction, followed by the support vector machine for multiple classes to classify medical images from multi-classes, which is used as the main classifier. Our proposed classification method was implemented on Kvasir and PH2 medical image datasets. The overall accuracy was 93.38% and 91.67% for Kvasir and PH2 datasets, respectively. The classification results and performance of our proposed method outperformed some of the related similar methods in this area of study.

A method for preventing online games hacking using memory monitoring

  • Lee, Chang Seon;Kim, Huy Kang;Won, Hey Rin;Kim, Kyounggon
    • ETRI Journal
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    • v.43 no.1
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    • pp.141-151
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    • 2021
  • Several methods exist for detecting hacking programs operating within online games. However, a significant amount of computational power is required to detect the illegal access of a hacking program in game clients. In this study, we propose a novel detection method that analyzes the protected memory area and the hacking program's process in real time. Our proposed method is composed of a three-step process: the collection of information from each PC, separation of the collected information according to OS and version, and analysis of the separated memory information. As a result, we successfully detect malicious injected dynamic link libraries in the normal memory space.

Comprehensive Analysis and Evaluation of Mobile S-MAC Protocol in Wireless Sensor Network

  • Alanazi, Adwan Alownie
    • International Journal of Computer Science & Network Security
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    • v.22 no.4
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    • pp.358-366
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    • 2022
  • Wireless sensor networks (WSN) are becoming widely used in collecting and sensing information in different fields such as in the medical area, smart phone industry and military environment. The main concern here is reducing the power consumption because it effects in the lifetime of wireless sensor during commutation because it may be work in some environment like sensor in the battlefields where is not easy to change the battery for a node and that may decrease the efficiency of that node and that may affect the network traffic may be interrupted because one or more nodes stop working. In this paper we implement, simulate, and investigate S-MAC protocol with mobility support and show the sequence of events the sender and receiver go through. We tested some parameters and their impacts of on the performance including System throughput, number of packets successfully delivered per second, packet delay, average packet delay before successful transmission.

Femtocell Networks Interference Management Approaches

  • Alotaibi, Sultan
    • International Journal of Computer Science & Network Security
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    • v.22 no.4
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    • pp.329-339
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    • 2022
  • Small cells, particularly femtocells, are regarded a promising solution for limited resources required to handle the increasing data demand. They usually boost wireless network capacity. While widespread usage of femtocells increases network gain, it also raises several challenges. Interference is one of such concerns. Interference management is also seen as a main obstacle in the adoption of two-tier networks. For example, placing femtocells in a traditional macrocell's geographic area. Interference comes in two forms: cross-tier and co-tier. There have been previous studies conducted on the topic of interference management. This study investigates the principle of categorization of interference management systems. Many methods exist in the literature to reduce or eliminate the impacts of co-tier, cross-tier, or a combination of the two forms of interference. Following are some of the ways provided to manage interference: FFR, Cognitive Femtocell and Cooperative Resource Scheduling, Beamforming Strategy, Transmission Power Control, and Clustering/Graph-Based. Approaches, which were proposed to solve the interference problem, had been presented for each category in this work.

Inquiring Prescriptions Using Geographic Information System (GIS)

  • Osman, Asim Seedahmed Ali;Kalil, Eman Galaleldin Ahmed
    • International Journal of Computer Science & Network Security
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    • v.21 no.12spc
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    • pp.409-414
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    • 2021
  • Geographic Information Systems (GIS) is considered to be one of the most important technologies provided by the Internet in our era. GIS enables institutions and individuals to plan and make decisions in many fields. GIS assists in accessing new and updated information on planning process. GIS also enables determining distances such as length, width, area on a map, and allows analyzing and processing a large amount of data for the search of geographical characteristics of locations. This paper explains the concept of dispensing prescription through the specific code of drug on an electronic system using GIS technology. The proposed methodology aims to inform patients of all the prescriptions dispensed and to help individuals inquiring about prescription at the nearest pharmacy through GIS technology. This proposed methodology is considered significant in some cases, as the patient does not know price, specifications and pharmacy location where the drug required is available, thus increasing the time and effort cost that is spent searching for the prescription.

Using Machine Learning to Improve Evolutionary Multi-Objective Optimization

  • Alotaibi, Rakan
    • International Journal of Computer Science & Network Security
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    • v.22 no.6
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    • pp.203-211
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    • 2022
  • Multi-objective optimization problems (MOPs) arise in many real-world applications. MOPs involve two or more objectives with the aim to be optimized. With these problems improvement of one objective may led to deterioration of another. The primary goal of most multi-objective evolutionary algorithms (MOEA) is to generate a set of solutions for approximating the whole or part of the Pareto optimal front, which could provide decision makers a good insight to the problem. Over the last decades or so, several different and remarkable multi-objective evolutionary algorithms, have been developed with successful applications. However, MOEAs are still in their infancy. The objective of this research is to study how to use and apply machine learning (ML) to improve evolutionary multi-objective optimization (EMO). The EMO method is the multi-objective evolutionary algorithm based on decomposition (MOEA/D). The MOEA/D has become one of the most widely used algorithmic frameworks in the area of multi-objective evolutionary computation and won has won an international algorithm contest.

Modern Problems And Prospects Of Distance Educational Technologies

  • Mykolaiko, Volodymyr;Honcharuk, Vitalii;Gudmanian, Artur;Kharkova, Yevdokia;Kovalenko, Svitlana;Byedakova, Sofiia
    • International Journal of Computer Science & Network Security
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    • v.22 no.9
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    • pp.300-306
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    • 2022
  • The theoretical analysis and synthesis of prospects for the development of distance learning in Ukraine, the main topical problems of distance education in Ukraine are considered, the main factors that hinder the introduction of distance learning are analyzed, to pay attention to the need to increase the level of computer literacy among Ukrainian educators and the formation of modern methodology of distance learning, in particular, a single, systematic, national approach of organization, coordination and control in this area. Research methods: analytical method, method of structural and functional analysis, phenomenological method, content analysis method, philosophical reflection method, sociological methods (questionnaire, interview).

Modeling and Simulation of the Photocatalytic Treatment of Wastewater using Natural Bauxite and TiO2 doped by Quantum Dots

  • Becheikh, Nidhal;Eladeb, Aboulbaba;Ghazouani, Nejib
    • International Journal of Computer Science & Network Security
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    • v.22 no.6
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    • pp.91-96
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    • 2022
  • The photocatalytic degradation of salicylic acid takes place in several stages involving coupled phenomena, such as the transport of molecules and the chemical reaction. The systems of transport equations and the photocatalytic reaction are numerically solved using COMSOL Mutiphysics (CM) simulation software. CM will make it possible to couple the phenomena of flow, the transport of pollutants (salicylic acid) by convection and diffusion, and the chemical reaction to the catalytic area (bauxite or TiO2 doped by nanoparticles). The simulation of the conversion rate allows to correctly fit the experimental results. The temporal simulation shows that the reaction reaches equilibrium after a transitional stage lasting over one minute. The outcomes of the study highlight the importance of diffusion in the boundary layer and the usefulness of injecting micro-agitation into the microchannel flow. Under such conditions, salicylic acid degrades completely.

Examination of Required Functions in the PBNM Scheme for Multiple Domains as Cyber Physical System that Utilizes Data Science and AI

  • Kazuya Odagiri;Shogo Shimizu;Naohiro Ishii
    • International Journal of Computer Science & Network Security
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    • v.23 no.2
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    • pp.31-38
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    • 2023
  • In the current Internet system, there are many problems using anonymity of the network communication such as personal information leaks and crimes using the Internet system. This is why TCP/IP protocol used in Internet system does not have the user identification information on the communication data, and it is difficult to supervise the user performing the above acts immediately. As a study for solving the above problem, there is the study of Policy Based Network Management (PBNM). This is the scheme for managing a whole Local Area Network (LAN) through communication control for every user. In this PBNM, two types of schemes exist. As one scheme, we have studied theoretically about the Destination Addressing Control System (DACS) Scheme with affinity with existing internet. By applying this DACS Scheme to Internet system management, we will realize the policy-based Internet system management. In this paper, required functions in the PBNM Scheme for multiple domains as cyber physical system that utilizes data science and AI is examined.

A Quantitative Approach for Data Visualization in Human Resource Management

  • Bandar Abdullah AlMobark
    • International Journal of Computer Science & Network Security
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    • v.23 no.2
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    • pp.133-139
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    • 2023
  • As the old saying goes "a picture is worth a thousand words" data visualization is essential in almost every industry. Companies make Data-driven decisions and gain insights from visual data. However, there is a need to investigate the role of data visualization in human resource management. This review aims to highlight the power of data visualization in the field of human resources. In addition, visualize the latest trends in the research area of human resource and data visualization by conducting a quantitative method for analysis. The study adopted a literature review on recent publications from 2017 to 2022 to address research questions.