• Title/Summary/Keyword: Network Security Visualization

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Design and Implementation of a Pre-processing Method for Image-based Deep Learning of Malware (악성코드의 이미지 기반 딥러닝을 위한 전처리 방법 설계 및 개발)

  • Park, Jihyeon;Kim, Taeok;Shin, Yulim;Kim, Jiyeon;Choi, Eunjung
    • Journal of Korea Multimedia Society
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    • v.23 no.5
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    • pp.650-657
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    • 2020
  • The rapid growth of internet users and faster network speed are driving the new ICT services. ICT Technology has improved our way of thinking and style of life, but it has created security problems such as malware, ransomware, and so on. Therefore, we should research against the increase of malware and the emergence of malicious code. For this, it is necessary to accurately and quickly detect and classify malware family. In this paper, we analyzed and classified visualization technology, which is a preprocessing technology used for deep learning-based malware classification. The first method is to convert each byte into one pixel of the image to produce a grayscale image. The second method is to convert 2bytes of the binary to create a pair of coordinates. The third method is the method using LSH. We proposed improving the technique of using the entire existing malicious code file for visualization, extracting only the areas where important information is expected to exist and then visualizing it. As a result of experimenting in the method we proposed, it shows that selecting and visualizing important information and then classifying it, rather than containing all the information in malicious code, can produce better learning results.

Application Of Information Technologies In Network Mass Communication Media

  • Ulianova, Kateryna;Kovalova, Tetiana;Mostipan, Tetiana;Lysyniuk, Maryna;Parfeniuk, Ihor
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.344-348
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    • 2021
  • The article examines one of the most important means of visualization of mass information on the Internet - information graphics in the broadest sense of the term as a visual technology for presenting mass information. The main objectives of the article are to determine the genre-typological features of infographics and basic technological principles; identification of features of creation and use of information graphics in modern network. Certain benefits of online infographic editors include savings in resources and time. They allow the user, who has basic PC skills, to create standardized infographics based on their own data. In addition, the use of online services develops visual thinking, allows you to get an idea of quality criteria and current trends in infographics, as well as to gain initial experience in the visual presentation of data.

Applying Information and Communication Technologies as A Scope of Teaching Activities and Visualization Techniques for Scientific Research

  • Viktoriya L. Pogrebnaya;Natalia O. Kodatska;Viktoriia D. Khurdei;Vitalii M. Razzhyvin;Lada Yu. Lichman;Hennadiy A. Senkevich
    • International Journal of Computer Science & Network Security
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    • v.23 no.2
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    • pp.193-198
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    • 2023
  • The article focuses on the areas of education activities in using techniques for teaching and learning with information and communication technologies (ICTs), researching and analyzing the available ICTs, gearing the technologies to the specific psychological and pedagogical conditions, independently building and modeling ICTs, enlarging and developing their use in the learning environment. The visualization of scientific research has been determined to be part of the educational support for building students' ICT competence during teaching and learning and is essential to the methodology culture. There have been specified main tasks for pedagogy technologies (PTs) to develop the skills of adaptability to the global digital space in students, their effective database operation and using the data bases as necessary elements for learning and as part of professional training for research. We provided rationalization for implementing the latest ICTs into the Ukrainian universities' curricula, as well as creating modern methods for using the technologies in the learning / teaching process and scientific activities.

A Study to Hierarchical Visualization of Firewall Access Control Policies (방화벽 접근정책의 계층적 가시화 방법에 대한 연구)

  • Kim, Tae-yong;Kwon, Tae-woong;Lee, Jun;Lee, Youn-su;Song, Jung-suk
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.6
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    • pp.1087-1101
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    • 2020
  • Various security devices are used to protect internal networks and valuable information from rapidly evolving cyber attacks. Firewall, which is the most commonly used security device, tries to prevent malicious attacks based on a text-based filtering rule (i.e., access control policy), by allowing or blocking access to communicate between inside and outside environments. However, in order to protect a valuable internal network from large networks, it has no choice but to increase the number of access control policy. Moreover, the text-based policy requires time-consuming and labor cost to analyze various types of vulnerabilities in firewall. To solve these problems, this paper proposes a 3D-based hierarchical visualization method, for intuitive analysis and management of access control policy. In particular, by providing a drill-down user interface through hierarchical architecture, Can support the access policy analysis for not only comprehensive understanding of large-scale networks, but also sophisticated investigation of anomalies. Finally, we implement the proposed system architecture's to verify the practicality and validity of the hierarchical visualization methodology, and then attempt to identify the applicability of firewall data analysis in the real-world network environment.

A network traffic prediction model of smart substation based on IGSA-WNN

  • Xia, Xin;Liu, Xiaofeng;Lou, Jichao
    • ETRI Journal
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    • v.42 no.3
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    • pp.366-375
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    • 2020
  • The network traffic prediction of a smart substation is key in strengthening its system security protection. To improve the performance of its traffic prediction, in this paper, we propose an improved gravitational search algorithm (IGSA), then introduce the IGSA into a wavelet neural network (WNN), iteratively optimize the initial connection weighting, scalability factor, and shift factor, and establish a smart substation network traffic prediction model based on the IGSA-WNN. A comparative analysis of the experimental results shows that the performance of the IGSA-WNN-based prediction model further improves the convergence velocity and prediction accuracy, and that the proposed model solves the deficiency issues of the original WNN, such as slow convergence velocity and ease of falling into a locally optimal solution; thus, it is a better smart substation network traffic prediction model.

Information Technologies In Teaching: The Basis Of Students' Knowledge

  • Morska, Nataliia;Fedorenko, Olena;Davydova, Olha;Andreev, Vitaly;Bohatyryova, Galina;Shcherbakova, Nataliia
    • International Journal of Computer Science & Network Security
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    • v.21 no.2
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    • pp.44-53
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    • 2021
  • The paper proposes to consider information technologies and their application in the educational process as a preparation of presentation material for students of higher educational institutions. The definition and place of information technologies in the educational space are considered. The object of research of this work is the pedagogical technology of presentation of educational information, which substantiates the pedagogical technology of visualization of educational information in higher education, as well as determine its composition and structure. The practical side of pedagogical technology of educational information presentation is considered.

SuperDepthTransfer: Depth Extraction from Image Using Instance-Based Learning with Superpixels

  • Zhu, Yuesheng;Jiang, Yifeng;Huang, Zhuandi;Luo, Guibo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.10
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    • pp.4968-4986
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    • 2017
  • In this paper, we primarily address the difficulty of automatic generation of a plausible depth map from a single image in an unstructured environment. The aim is to extrapolate a depth map with a more correct, rich, and distinct depth order, which is both quantitatively accurate as well as visually pleasing. Our technique, which is fundamentally based on a preexisting DepthTransfer algorithm, transfers depth information at the level of superpixels. This occurs within a framework that replaces a pixel basis with one of instance-based learning. A vital superpixels feature enhancing matching precision is posterior incorporation of predictive semantic labels into the depth extraction procedure. Finally, a modified Cross Bilateral Filter is leveraged to augment the final depth field. For training and evaluation, experiments were conducted using the Make3D Range Image Dataset and vividly demonstrate that this depth estimation method outperforms state-of-the-art methods for the correlation coefficient metric, mean log10 error and root mean squared error, and achieves comparable performance for the average relative error metric in both efficacy and computational efficiency. This approach can be utilized to automatically convert 2D images into stereo for 3D visualization, producing anaglyph images that are visually superior in realism and simultaneously more immersive.

Shadow Libraries: A Bibliometric Analysis of Black Open Access Phenomenon (2011: 2023)

  • Safinaz Mahmoud Elroukh
    • International Journal of Computer Science & Network Security
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    • v.24 no.5
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    • pp.21-32
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    • 2024
  • This study analyzes the global literature on the black open-access phenomenon from 2011 to 2023. A bibliometric analysis was conducted using the Scopus database. The search strategy employed advanced queries with multiple synonymous terms to ensure exhaustive retrieval of relevant documents. The VOSviewer software was employed to visualize the co-occurrence networks. The findings reported 90 papers published during the study period. An evolving scholarly landscape was revealed, with heightened attention from 2016 onwards, peaking in 2017, 2021, and 2023. Articles constitute 83.3% of the total published documents. Singh and Srichandan are prolific authors, with 11.2% of the total publications. The United States contributes 18.9% of the papers, followed by India and Spain. Information Development and Scientometrics are pivotal journals in scholarly discussions about this scope, contributing 4.4% of publications. Co-occurrence network visualization revealed "Sci-Hub" and "open access" as the most used keywords in the global literature. The findings underscore the need for additional research to discover innovative business models to safeguard intellectual property rights while meeting researchers' evolving needs. The importance of this paper comes from being the first bibliometric study analyzing international literature related to this phenomenon, which provides a basis for future research efforts and policymaking.

Machine Learning based Prediction of The Value of Buildings

  • Lee, Woosik;Kim, Namgi;Choi, Yoon-Ho;Kim, Yong Soo;Lee, Byoung-Dai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.8
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    • pp.3966-3991
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    • 2018
  • Due to the lack of visualization services and organic combinations between public and private buildings data, the usability of the basic map has remained low. To address this issue, this paper reports on a solution that organically combines public and private data while providing visualization services to general users. For this purpose, factors that can affect building prices first were examined in order to define the related data attributes. To extract the relevant data attributes, this paper presents a method of acquiring public information data and real estate-related information, as provided by private real estate portal sites. The paper also proposes a pretreatment process required for intelligent machine learning. This report goes on to suggest an intelligent machine learning algorithm that predicts buildings' value pricing and future value by using big data regarding buildings' spatial information, as acquired from a database containing building value attributes. The algorithm's availability was tested by establishing a prototype targeting pilot areas, including Suwon, Anyang, and Gunpo in South Korea. Finally, a prototype visualization solution was developed in order to allow general users to effectively use buildings' value ranking and value pricing, as predicted by intelligent machine learning.

Analysis of 3D Building Construction Applications in Augmented Reality

  • Khan, Humera Mehfooz;Waseemullah, Waseemullah;Bhutto, Muhammad Aslam;Khan, Shariq Mahmood;Baig, Mirza Adnan
    • International Journal of Computer Science & Network Security
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    • v.22 no.10
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    • pp.340-346
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    • 2022
  • Construction industry is considered as one of the oldest industries in the world since human came into being and the need of their own space is realized. All this led to make the world a space of many beautiful constructive ventures. As per the requirements of today's world, every industry is recognizing the need for use and adoption of modern as well as innovative technologies due to their benefits and timely production. Now construction industry has also started adopting the use of modern and innovative technologies during their projects but still the rate of adoption is so slow. From design to completion, construction projects take a lot to manage for which technology based solutions have continuously been proposed. These include Computer Aided Design (CAD), building information modeling (BIM) and cloud computing have been proved to be much successful until now. The construction projects are high budgeted, and direly require timely and successful completion with quality, resource and other constraints. So, the researchers observe the need of more clear and technology based communication between the construction projects and its constructors and other stakeholders is required before and during the construction to take timely precautions for expected issues. This study has analyzed the use of Augmented Reality (AR) technology adopting GammaAR, and ARki applications in construction industry. It has been found that both applications are light-weighted, upgradable, provide offline availability and collaborative environment as well as fulfil most of the requirements of the construction industry except the cost. These applications also support different screen size for better visualization and deep understanding. Both applications are analyzed, based on construction's application requirements, usability of AR and ratings of applications user collected from application's platform. The purpose of this research is to provide a detail insight of construction applications which are using AR to facilitate both the future developers and consumers.