• Title/Summary/Keyword: 정보보안모델

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AI Security Plan for Public Safety Network App Store (재난안전통신망 앱스토어를 위한 AI 보안 방안 마련)

  • Jung, Jae-eun;Ahn, Jung-hyun;Baik, Nam-kyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.458-460
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    • 2021
  • The provision and application of public safety network in Korea is still insufficient for security response to the mobile app of public safety network in the stages of development, initial construction, demonstration, and initial service. The available terminals on the Disaster Safety Network (PS-LTE) are open, Android-based, dedicated terminals that potentially have vulnerabilities that can be used for a variety of mobile malware, requiring preemptive responses similar to FirstNet Certified in U.S and Google's Google Play Protect. In this paper, before listing the application service app on the public safety network mobile app store, we construct a data set for malicious and normal apps, extract features, select the most effective AI model, perform static and dynamic analysis, and analyze Based on the result, if it is not a malicious app, it is suggested to list it in the App Store. As it becomes essential to provide a service that blocks malicious behavior app listing in advance, it is essential to provide authorized authentication to minimize the security blind spot of the public safety network, and to provide certified apps for disaster safety and application service support. The safety of the public safety network can be secured.

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Study on the Appropriate Use of Weapons by Private Security Guards: Focusing on Public Crowded Places (민간 경비원(보안요원)의 정당한 무기사용 방안 연구: 다중이용시설을 중심으로)

  • Hangil Oh;Kyewon Ahn;Ye ji Na
    • Journal of the Society of Disaster Information
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    • v.19 no.4
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    • pp.936-949
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    • 2023
  • On August 3, 2023, a brutal incident of unprovoked violence, termed as "Abnormal motivated crime," occurred in a multi-use facility, where retail and transportation facilities converge, near Seohyeon Station. The assailant drove onto the sidewalk, hitting pedestrians, and then entered a department store where a knife rampage ensued, resulting in a total of 14 victims. In the aftermath of this incident, numerous murder threats were posted on social media, causing widespread anxiety among the public. This fear was further exacerbated by the emergence of a "Terrorless.01ab.net" service. Purpose: This research aims to explore necessary institutional improvements for private security personnel who protect customers and employees in multi-use facilities, to enable them to perform their duties more effectively. Method: To assess the risk of Abnormal motivated crime, a time series analysis using the ARIMA model was conducted to analyze the domestic trends of such crimes. Additionally, Result: the study presents suggestions for improvements in the domestic security service law and emergency manuals for multi-use facilities. Conclusion: This is informed by a legal analysis of the indemnity rights for weapon use by private security guards abroad and their operational authority beyond weapon usage.

Dynamic Predicate: An Efficient Access Control Mechanism for Hippocratic XML Databases (동적 프레디킷 : 허포크라테스 XML 데이타베이스를 위한 효율적인 액세스 통제 방법)

  • Lee Jae-Gil;Han Wook-Shin;Whang Kyu-Young
    • Journal of KIISE:Databases
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    • v.32 no.5
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    • pp.473-486
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    • 2005
  • The Hippocratic database model recently proposed by Agrawal et at. incorporates privacy protection capabilities into relational databases. The authors have subsequenty proposed the Hippocratic XML daかabase model[4], an extension of the Hippocratic database model for XML databases. In this paper, we propose a new concept that we cail the dynamic predicate(DP) for effective access control in the Hippocratic XML database model. A DP is a novel concept that represents a dynamically constructed rendition that tan be adapted for determining the accessibility of elements during query execution. DPs allow us to effectively integrate authorization checking into the query plan so that unauthorized elements are excluded in the process of query execution. Using synthetic and real data, we have performed extensive experiments comparing query processing time with those of existing access control mechanisms. The results show that the proposed access control mechanism improves the wall clock time by up to 219 times over the top-down access control strategy and by up to 499 times over the bottom-up access control strategy. The major contribution of our, paper is enabling effective integration of access control mechanisms with the query plan using the DP under the Hippocratic XML database model.

A Research on Network Intrusion Detection based on Discrete Preprocessing Method and Convolution Neural Network (이산화 전처리 방식 및 컨볼루션 신경망을 활용한 네트워크 침입 탐지에 대한 연구)

  • Yoo, JiHoon;Min, Byeongjun;Kim, Sangsoo;Shin, Dongil;Shin, Dongkyoo
    • Journal of Internet Computing and Services
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    • v.22 no.2
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    • pp.29-39
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    • 2021
  • As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.

The Internet GIS Infrastructure for Interoperablility : MAP(Mapping Assistant Protocol) (상호운용을 위한 인터넷 GIS 인프라구조 : MAP(Mapping Assistant Protocol))

  • 윤석찬;김영섭
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10a
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    • pp.424-426
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    • 1998
  • 공간정보의 효율적 공유를 위해 인터넷 기반 GIS소프트웨어 개발 및 응용과 관련된 연구가 활발히 진행 중에 있다. 여러 인터넷 GIS의 기본적인 요구사항 및 현재까지 개발모델과 문제점을 살펴보고, 표준 인터넷 기술을 기반으로 최근 웹 기술 표준 동향을 포함한, OpenGIS상호 운용성이 지원되는 인터넷 GIS기본 구조를 제시하고자 한다. 표준화될 인터넷 GIS 속도 향상과 TCP/IP상의 보안문제가 해결되어야 하고, OpenGIS에서 구성하고 있는 공간 데이터 공유를 위한 표준 사양을 준수할 뿐 아니라 클라이언트/서버의 부하가 최적화된 구조여야한다. 특히 웹 중심의 각종 인터넷 기술들, 즉 HTTP NG. XML, SSL등의 표준 기술이 함께 적용되어야 한다. 새로운 인프라구조는 GIS D/B에 포함된 확장된 (Enhanced) HTTP/MAP 서버와 클라이언트로 구성된다. MAP클라이언트는 MIME-TYPE 에 따라 GIS데이터를 표시할 수 있는 윈도우 환경으로 변환되며 GIS 데이터셋은 XML을 기반으로 하는 MapML(Mapping Makup Language)를 통해 형식을 정한다. 클라이언트가 MapML 토큐먼트를 통해 정의된 구획의 레이어와 벡터 데이터를 요청하고, Map서버는GIS D/B에서 WKB 혹은 소위 VML 형태로 추출하여 클라이언트로 보내주게 된다. 주어진 구획은 MapML로 정의된 속성들을 통해 각종 부가 정보를 열람할 수 있다. MAP은 HTTP와 같은 형태로 동작하므로 전자인증, 암호화를 통한 GIS정보 보안, 클라이언트와 서버 부하의 효율적인 분배 XML을 통한 다양한 GIS속성표현이 가능하다. 본 구조는 Apache +Amiya + Crass D/B+ MapML 환경에서 구현되고 있다.팔일 전송 기법을 각각 제시하고 실험을 통해 이들의 특성을 비교분석하였다.미에서 uronic acid 함량이 두 배 이상으로 나타났다. 흑미의 uronic acid 함량이 가장 많이 용출된 분획은 sodium hydroxide 부분으로서 hemicellulose구조가 polyuronic acid의 형태인 것으로 사료된다. 추출획분의 구성단당은 여러 곡물연구의 보고와 유사하게 glucose, arabinose, xylose 함량이 대체로 높게 나타났다. 점미가 수가용성분에서 goucose대비 용출함량이 고르게 나타나는 경향을 보였고 흑미는 알칼리가용분에서 glucose가 상당량(0.68%) 포함되고 있음을 보여주었고 arabinose(0.68%), xylose(0.05%)도 다른 종류에 비해서 다량 함유한 것으로 나타났다. 흑미는 총식이섬유 함량이 높고 pectic substances, hemicellulose, uronic acid 함량이 높아서 콜레스테롤 저하 등의 효과가 기대되며 고섬유식품으로서 조리 특성 연구가 필요한 것으로 사료된다.리하였다. 얻어진 소견(所見)은 다음과 같았다. 1. 모년령(母年齡), 임신회수(姙娠回數), 임신기간(姙娠其間), 출산시체중등(出産時體重等)의 제요인(諸要因)은 주산기사망(周産基死亡)에 대(對)하여 통계적(統計的)으로 유의(有意)한 영향을 미치고 있어 $25{\sim}29$세(歲)의 연령군에서, 2번째 임신과 2번째의 출산에서 그리고 만삭의 임신 기간에, 출산시체중(出産時體重) $3.50{\sim}3.99kg$사이의 아이에서 그 주산기사망률(周産基死亡率)이 각각 가장 낮았다. 2. 사산(死産)과 초생아사망(初生兒死亡)을 구분(區分)하여 고려해 볼때 사산(死産)은 모성(母

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Effect of Block chain Characteristic on Acceptance Intention: Focusing on Medical Area (블록체인 특성이 수용의도에 미치는 영향 : 의료분야를 중심으로)

  • Park, Jung-Hong;Kim, Jinsu
    • The Journal of the Korea Contents Association
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    • v.20 no.4
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    • pp.169-180
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    • 2020
  • In this study, we explored Technology Acceptance Model(TAM) to introduce Blockchain technology in the medical field. It extracted five external variables(Security, Availability, Reliability, Diversity, Economic feasibility) through previous studies. It set the study model for a path to acceptance intention through the information reliance of recognized easiness and recognized usefulness. As results of empirical analysis, H1-1(Security →Perceived Easiness) was rejected. H1-2(Availability→Perceived Easiness), H1-3(Reliabilit→Perceived Easiness), H1-4(Diversity →Perceived Easiness), H1-5(Economic →Perceived Easiness) were adopted. Hypothesis 2 was a relations between Blockchain's characteristics and Perceived usefulness, all the Hypothesis were adopted. Hypothesis 3 and Hypothesis 4 indicated that H3-1(Perceived Easiness →Perceived usefulness) was rejected but H3-2(Perceived Easiness → information reliability), H3-3(Perceived usefulness → information reliability), and H4(information reliability→acceptance intention) were all adopted. It was confirmed that it is important to emphasize the importance of stability to introduce block chain technology to medical centers, but it was necessary to use a design that can increase the easiness from the prospect of users.

A Design and Implementation of Anomaly Detection Model based the Web Traffic Trend Analysis (웹 트래픽 추이 분석 기반 비정상행위 탐지 모델의 설계 및 구현)

  • Jang, Sung-Min;Park, Soon-Dong
    • Journal of the Korea Computer Industry Society
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    • v.6 no.5
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    • pp.715-724
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    • 2005
  • Recently many important systems that used to be operated in a closed environment are now providing web services and these kinds of web-based services are often an easy and common target of attacks. In addition, the great variety of web content and applications cause the development of new various intrusion technologies, while the misuse-based intrusion detection technology cannot keep the peace with the attacks and it seems to lack the capability to deal with such various new security threats, As a result it is necessary to research and develop new types of detection technologies that can detect newly developed attacks and intrusions as well as to be able to deal with previous types of exploits. In this paper, a HTTP traffic model is tested for its anomaly by using a HTTP request traffic pattern analysis and the field information analysis of the HTTP packet. Consequently, the HTTP traffic models by applying anomaly tests is designed and established.

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An Algorithm for Referential Integrity Relations Extraction using Similarity Comparison of RDB (유사성 비교를 통한 RDB의 참조 무결성 관계 추출 알고리즘)

  • Kim, Jang-Won;Jeong, Dong-Won;Kim, Jin-Hyung;Baik, Doo-Kwon
    • Journal of the Korea Society for Simulation
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    • v.15 no.3
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    • pp.115-124
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    • 2006
  • XML is rapidly becoming technologies for information exchange and representation. It causes many research issues such as semantic modeling methods, security, conversion far interoperability with other models, and so on. Especially, the most important issue for its practical application is how to achieve the interoperability between XML model and relational model. Until now, many suggestions have been proposed to achieve it. However several problems still remain. Most of all, the exiting methods do not consider implicit referential integrity relations, and it causes incorrect data delivery. One method to do this has been proposed with the restriction where one semantic is defined as only one same name in a given database. In real database world, this restriction cannot provide the application and extensibility. This paper proposes a noble conversion (RDB-to-XML) algorithm based on the similarity checking technique. The key point of our method is how to find implicit referential integrity relations between different field names presenting one same semantic. To resolve it, we define an enhanced implicity referentiai integrity relations extraction algorithm based on a widely used ontology, WordNet. The proposed conversion algorithm is more practical than the previous-similar approach.

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Internet of Things and Innovative Media Firms (사물인터넷과 미디어기업의 혁신)

  • Moon, Sanghyun
    • Journal of the Korea Convergence Society
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    • v.10 no.6
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    • pp.157-164
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    • 2019
  • This research examines how IoT makes a significant contribution to the innovation of media firms. The media firms will be able to find new reveue sources and strengthen firms' competence through innovating product, process and business model. While IoT increases the experience of interactivity and immersion for consumption, it improves the way ads are exposed and its impact is measured, leading to revenue increase. For these benefits fulfilled, innovation friendly media eco-system must be established. It is the most critical that media firms should change skeptical attitude toward IoT's potential and actively invest it to employ IoT. The government should create regulatory framework to best utilize the innovative advantages of IoT.

Improving prediction performance of network traffic using dense sampling technique (밀집 샘플링 기법을 이용한 네트워크 트래픽 예측 성능 향상)

  • Jin-Seon Lee;Il-Seok Oh
    • Smart Media Journal
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    • v.13 no.6
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    • pp.24-34
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    • 2024
  • If the future can be predicted from network traffic data, which is a time series, it can achieve effects such as efficient resource allocation, prevention of malicious attacks, and energy saving. Many models based on statistical and deep learning techniques have been proposed, and most of these studies have focused on improving model structures and learning algorithms. Another approach to improving the prediction performance of the model is to obtain a good-quality data. With the aim of obtaining a good-quality data, this paper applies a dense sampling technique that augments time series data to the application of network traffic prediction and analyzes the performance improvement. As a dataset, UNSW-NB15, which is widely used for network traffic analysis, is used. Performance is analyzed using RMSE, MAE, and MAPE. To increase the objectivity of performance measurement, experiment is performed independently 10 times and the performance of existing sparse sampling and dense sampling is compared as a box plot. As a result of comparing the performance by changing the window size and the horizon factor, dense sampling consistently showed a better performance.