• Title/Summary/Keyword: Text Security

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An Empirical Study for Efficient Preparation for Enhancing North Korean Nuclear Threat: Focusing on non-military field (북핵 위협 고도화에 효율적 대비를 위한 실증적 연구: 비군사 분야를 중심으로)

  • Kim, Eung-Soo
    • Korean Security Journal
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    • no.53
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    • pp.255-279
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    • 2017
  • The development of North Korea's nuclear weapons has worsened to the sixth nuclear test in 2017, and despite the sanctions of the international community including our government, we have not been able to offer clear solutions and alternatives, and the current measures are not enough in case of North Korea is using nuclear weapons. This study suggests how we should be prepared against the use of nuclear weapons under the premise that North Korea will never give up development of nuclear weapons under any circumstances. The first chapter outlines the current status of our preparedness if North Korea makes a nuclear attack. The second chapter analyzes and evaluates the power of nuclear weapons and North Korea's nuclear weapons threat. In the third chapter, we analyze North Korea nuclear attack and analyze the wartime emergency situation and civil defense posture. Finally, in order to implement the solutions presented in the text, we will identify priorities and summarize further developments.

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A domain-specific sentiment lexicon construction method for stock index directionality (주가지수 방향성 예측을 위한 도메인 맞춤형 감성사전 구축방안)

  • Kim, Jae-Bong;Kim, Hyoung-Joong
    • Journal of Digital Contents Society
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    • v.18 no.3
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    • pp.585-592
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    • 2017
  • As development of personal devices have made everyday use of internet much easier than before, it is getting generalized to find information and share it through the social media. In particular, communities specialized in each field have become so powerful that they can significantly influence our society. Finally, businesses and governments pay attentions to reflecting their opinions in their strategies. The stock market fluctuates with various factors of society. In order to consider social trends, many studies have tried making use of bigdata analysis on stock market researches as well as traditional approaches using buzz amount. In the example at the top, the studies using text data such as newspaper articles are being published. In this paper, we analyzed the post of 'Paxnet', a securities specialists' site, to supplement the limitation of the news. Based on this, we help researchers analyze the sentiment of investors by generating a domain-specific sentiment lexicon for the stock market.

A design of Key Exchange Protocol for User Centered Home Network (사용자 중심의 홈네트워크를 위한 키 교환 프로토콜 설계)

  • 정민아
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.3
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    • pp.654-660
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    • 2004
  • In this paper, we define that pervasive home network, which provides necessary services for user properties and removes distractions to improve the quality of human life. So, user can enjoy home network technology including devices and softwares at any place with no knowledge of networked home, devices, and softwares. In this home network, a mobile agent, called LAFA, can migrate to unfamiliar home network and control the necessary devices. For this environment, we design security management module for authenticating user and home server that access some other home networks, and for protecting text, multimedia data, and mobile agent that are transferred between home networks. The security management module is composed of a key exchange management module and an access control management module, for key exchange management module, we propose a key exchange protocol, which provides multimode of authentication mode and key exchange mode. One of these two modes is selected according to the data type.

Traffic Data Generation Technique for Improving Network Attack Detection Using Deep Learning (네트워크 공격 탐지 성능향상을 위한 딥러닝을 이용한 트래픽 데이터 생성 연구)

  • Lee, Wooho;Hahm, Jaegyoon;Jung, Hyun Mi;Jeong, Kimoon
    • Journal of the Korea Convergence Society
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    • v.10 no.11
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    • pp.1-7
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    • 2019
  • Recently, various approaches to detect network attacks using machine learning have been studied and are being applied to detect new attacks and to increase precision. However, the machine learning method is dependent on feature extraction and takes a long time and complexity. It also has limitation of performace due to learning data imbalance. In this study, we propose a method to solve the degradation of classification performance due to imbalance of learning data among the limit points of detection system. To do this, we generate data using Generative Adversarial Networks (GANs) and propose a classification method using Convolutional Neural Networks (CNNs). Through this approach, we can confirm that the accuracy is improved when applied to the NSL-KDD and UNSW-NB15 datasets.

Improvement of Satellite Ocean Information Service for Offshore Marine Industry (연근해 해양산업을 위한 위성해양 정보 서비스 개선방안)

  • Cho, Bo-Hyun;Lee, Gun-Wook;Kim, Dong-Chun;Yang, Keum-Cheol;Kim, SG;Yo, Seung-jae
    • Convergence Security Journal
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    • v.18 no.1
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    • pp.85-91
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    • 2018
  • In this study, we design a marine environmental information service system with satellite images based on satellite images to reduce the damage caused by changes in the marine environment. The system provides satellite oceanographic information such as water temperature, chlorophyll, float, etc. as hierarchical texts, which is implemented as a unit module Web service so that it can be expanded in OpenAPI environment. And stability of system plug-in portability, service hours, data extraction precision and speed are used as a basis for diagnosing service stability. By securing the function and performance of the service system implemented in this study, it can be expanded to a complex technology that can customize the users by group by adding not only general services of existing systems operated by location but also information about a specific interested areas. Especially, various other items of interest including marine environment information are developed in modules, so we expect to be able to expand and service the system by plugging into the system and to spread it in technical linkage with the related institution information system.

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Development of Integrated Computational Fluid Dynamics(CFD) Environment using Opensource Code (오픈소스 코드를 이용한 통합 전산유체역학 환경 구축)

  • Kang, Seunghoon;Son, Sungman;Oh, Se-Hong;Park, Wonman;Choi, Choengryul
    • Convergence Security Journal
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    • v.18 no.1
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    • pp.33-42
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    • 2018
  • CFD analysis is an analytical technique that applies a computer to the design and development of products across the entire industry for heat or fluid flow. This technology is used to shorten the development period and reduce costs through computerized simulation. However, the software used for CFD analysis is now required to use expensive foreign software. The Opensource CFD analysis software used in the proposed system has reliability of commercial CFD analysis software and has various user groups. However, for users who have expert knowledge, Opensource CFD software which supports only text interface environment, We have developed an environment that enables the construction of a CFD analysis environment for beginners as well as professionals. In addition, the proposed system supports the pre-processing (design and meshing) environment for CFD analysis and the environment for post-processing (result analysis & visualization), enabling the integrated CFD analysis process in one platform.

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A Study on the Perception of Data 3 Act through Big Data Analysis (빅데이터 분석을 통한 데이터 3법 인식에 관한 연구)

  • Oh, Jungjoo;Lee, Hwansoo
    • Convergence Security Journal
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    • v.21 no.2
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    • pp.19-28
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    • 2021
  • Korea is promoting a digital new deal policy for the digital transformation and innovation accelerating of the industry. However, because of the strict existing data-related laws, there are still restrictions on the industry's use of data for the digital new deal policy. In order to solve this issue, a revised bill of the Data 3 Act has been proposed, but there is still insufficient discussion on how it will actually affect the activation of data use in the industry. Therefore, this study aims to analyze the perception of public opinion on the Data 3 Act and the implications of the revision of the Data 3 Act. To this end, the revision of the Data 3 Act and related research trends were analyzed, and the perception of the Data 3 Act was analyzed using a big data analysis technique. According to the analysis results, while promoting the vitalization of the data industry in line with the purpose of the revision, the Data 3 Act has a concern that it focuses on specific industries. The results of this study are meaningful in providing implications for future improvement plans by analyzing online perceptions of the industrial impact of the Data 3 Act in the early stages of implementation through big data analysis.

An Improved Round Reduction Attack on Triple DES Using Fault Injection in Loop Statement (반복문 오류 주입을 이용한 개선된 Triple DES 라운드 축소 공격)

  • Choi, Doo-Sik;Oh, Doo-Hwan;Park, Jeong-Soo;Ha, Jae-Cheol
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.22 no.4
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    • pp.709-717
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    • 2012
  • The round reduction on block cipher is a fault injection attack in which an attacker inserts temporary errors in cryptographic devices and extracts a secret key by reducing the number of operational round. In this paper, we proposed an improved round reduction method to retrieve master keys by injecting a fault during operation of loop statement in the Triple DES. Using laser fault injection experiment, we also verified that the proposed attack could be applied to a pure microprocessor ATmega 128 chip in which the Triple DES algorithm was implemented. Compared with previous attack method which is required 9 faulty-correct cipher text pairs and some exhaustive searches, the proposed one could extract three 56-bit secret keys with just 5 faulty cipher texts.

Smart Deaf Emergency Application Based on Human-Computer Interaction Principles

  • Ahmed, Thowiba E;Almadan, Naba Abdulraouf;Elsadek, Alma Nabil;Albishi, Haya Zayed;Al-Qahtani, Norah Eid;Alghamdi, arah Khaled
    • International Journal of Computer Science & Network Security
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    • v.21 no.4
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    • pp.284-288
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    • 2021
  • Human-computer interaction is a discipline concerned with the design, evaluation, and implementation of interactive systems for human use. In this paper we suggest designing a smart deaf emergency application based on Human-Computer Interaction (HCI) principles whereas nowadays everything around us is becoming smart, People already have smartphones, smartwatches, smart cars, smart houses, and many other technologies that offer a wide range of useful options. So, a smart mobile application using Text Telephone or TeleTYpe technology (TTY) has been proposed to help people with deafness or impaired hearing to communicate and seek help in emergencies. Deaf people find it difficult to communicate with people, especially in emergency status. It is stipulated that deaf people In all societies must have equal rights to use emergency services as other people. With the proposed application the deafness or impaired hearing can request help with one touch, and the location will be determined, also the user status will be sent to the emergency services through the application, making it easier to reach them and provide them with assistance. The application contains several classifications and emergency status (traffic, police, road safety, ambulance, fire fighting). The expected results from this design are interactive, experiential, efficient, and comprehensive features of human-computer interactive technology which may achieve user satisfaction.

Analysis of Research Topics and Trends on COVID-19 in Korea Using Latent Dirichlet Allocation (LDA)

  • Heo, Seong-Min;Yang, Ji-Yeon
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.12
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    • pp.83-91
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    • 2020
  • This study aims to identify research topics and examine the trend of Covid19-related papers on DBpia. Applying latent Dirichlet allocation (LDA), we have extracted seven research topics, each of which concerns "International Dynamics", "Technology & Security", "Psychological Impact", "Biomedical-Related", "Economic Impact", "Online Education", and "Religion-Related". In addition, we used the multinomial logistic model to examine the trend of research topics. We found that the papers mainly cover topics related to "International Dynamics" and "Biomedical-Related" before June 2020, but the topics have become diverse since then. In particular, topics regarding "Economic Impact", "Online Education" and "Psychological Impact" has drawn increased attention of researchers. The findings would provide a guideline for collaboration in Covid19-related research, and could serve as a reference work for active research.