• Title/Summary/Keyword: 동적 테스트 데이터 생성

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Research on File-based Malware Detection Method (악성코드 파일기반 탐지방법에 대한 연구)

  • Yoon, Ju Young;Kim, Sang Hoon;Kim, Seun O
    • Annual Conference of KIPS
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    • 2020.11a
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    • pp.370-373
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    • 2020
  • 본 연구는 파일기반 악성파일 탐지시간을 줄이는 알고리즘 사용에 대해 기술하고 있다. 기존 탐지방식은 파일의 시그니처 값에 대한 유사도를 단순히 비교하는 것에만 그쳐 오탐율이 높거나 새롭게 생성되는 악성파일을 대응할 수 없는 제한점이 있다. 또한 정확도를 높이고자 딥 러닝을 통한 탐지방식이 제안되고 있으나 이 또한 동적분석으로 진행이 되기 때문에 시간이 오래 걸리는 제한이 있다. 그래서 우리는 이를 보완하는 VP Tree 탐지를 제안한다. 이 방법은 시그니처 값이 아닌 다차원에서의 해시 값의 데이터 위치를 기반으로 거리를 척도 한다. 유클리드 거리 법, 맨해튼 거리법이 사용되며 삼각부등식의 만족하는 기준으로 K-NN 이 생성이 되며, K-NN 을 이진 트리로 구성하여 인덱스를 통한 탐지를 진행하기에 기존 방법들을 보완할 수 있는 대안점이 될 수 있으며, 악성파일과 정상파일이 섞여 존재하는 총 3 만개의 데이터를 대상으로 악성파일 탐지 테스트를 진행하였으며 기본 방식에 비해 약 15~20%정도 속도가 단축된다는 것을 입증했다.

The Development of the Application Program Generator based on Meta-Data (메타데이터를 이용한 응용프로그램 생성기의 개발)

  • Kim Chi-Su
    • The KIPS Transactions:PartD
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    • v.13D no.1 s.104
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    • pp.97-102
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    • 2006
  • Generally, a software development process is composed with requirements analysis, design, coding, test and maintenance. However, some changes of the design step are difficult to complicate the next step in the development process. It always causes the disagreement between design and implementation step. In this paper, we have developed a tool which can generate an application program. The tool can reduce the disagreement between system design and implementation and recognize the business logic to develop the software rapidly and flexibly In addition, we proposed a non-program-based application program system approach was proposed, In. We can generate and modify an application program with this method which can edit the meta data of a system design by the dynamic method for the execution time.

Development of bigdata service brokers for bigdata analysis service operation and management (빅데이터 분석 서비스 운영 관리를 위한 빅데이터 서비스 브로커 설계 및 개발)

  • Kim, Baul;Kim, Sanggyu;Kim, Subin;Koo, Wonbon
    • Annual Conference of KIPS
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    • 2021.11a
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    • pp.125-127
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    • 2021
  • 본 논문에서는 기존의 산업 및 서비스 변화에 따라 발생하는 빅데이터 분석 서비스 처리를 위한 빅데이터 분석 서비스 브로커 시스템을 제안한다. 기존의 빅데이터 분석 시스템은 분석하는 시간 동안 지속적으로 자원을 점유하고 있어야 하며, 이러한 서비스를 이용하기 위해 내부에 대규모의 시스템을 구축하고 지속적으로 운영해야하는 단점이 존재한다. 본 논문에서는 빅데이터 분석에 필요한 자원을 효과적으로 사용하기 위해 클라우드 기반의 자원 관리와 연계하고 서비스 이용을 용이하게 하기 위해 단일 엔드포인트 기반의 빅데이터 분석 서비스 호출 구조를 설계하였다. 이를 통해 빅데이터 서비스 분석에 소요되는 자원 점유에 따라 동적으로 자원을 생성 관리하여 자원을 보다 효과적으로 이용할 수 있는지 테스트베드를 구축하여 서비스 이용 및 자원 사용을 효과적으로 하는지 확인하였다. 또한, 이를 통해 대규모 자원을 지속적으로 점유해야하는 빅데이터 분석 플랫폼의 자원사용에 대한 한계를 일부 해소하여 자원을 효과적으로 이용할 수 있는 것을 확인하였다.

The class testing based on a dependence graph (종속성 그래프 기반 클래스 테스팅)

  • Im, Dong-Ju;Bae, Sang-Hyun
    • Journal of Internet Computing and Services
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    • v.1 no.1
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    • pp.105-113
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    • 2000
  • The representation of a procedural program cannot be applied directly to object oriented program representation consisting of class, object, inheritance, and dynamic binding. Furthermore, preexisting program dependence represented the dependence among statements, but not among variables. That is, it could not solve the problem of which variables make an effect on given variables. Consequently, this study presents the method dependence model representing implementation level information including the dependence among variables in an object oriented program. I also propose implementation-based class testing technique based on the test adequacy criterion of an object-oriented program. Considering inter-data member dependences and a set of axioms for test data adequacy, it generates sequences of methods as test cases which satisfy a flow graph-based testing criterion. For a derived class testing, it considers inheritance relationship and the resuability of the testing information for its parent classes which verified the reduction of test cost through the experiment.

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Enhancing Classification Performance of Temporal Keyword Data by Using Moving Average-based Dynamic Time Warping Method (이동 평균 기반 동적 시간 와핑 기법을 이용한 시계열 키워드 데이터의 분류 성능 개선 방안)

  • Jeong, Do-Heon
    • Journal of the Korean Society for information Management
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    • v.36 no.4
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    • pp.83-105
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    • 2019
  • This study aims to suggest an effective method for the automatic classification of keywords with similar patterns by calculating pattern similarity of temporal data. For this, large scale news on the Web were collected and time series data composed of 120 time segments were built. To make training data set for the performance test of the proposed model, 440 representative keywords were manually classified according to 8 types of trend. This study introduces a Dynamic Time Warping(DTW) method which have been commonly used in the field of time series analytics, and proposes an application model, MA-DTW based on a Moving Average(MA) method which gives a good explanation on a tendency of trend curve. As a result of the automatic classification by a k-Nearest Neighbor(kNN) algorithm, Euclidean Distance(ED) and DTW showed 48.2% and 66.6% of maximum micro-averaged F1 score respectively, whereas the proposed model represented 74.3% of the best micro-averaged F1 score. In all respect of the comprehensive experiments, the suggested model outperformed the methods of ED and DTW.

Development of a Web-based Geovisualization System using Google Earth and Spatial DBMS (구글어스와 공간데이터베이스를 이용한 웹기반 지리정보 표출시스템 개발)

  • Im, Woo-Hyuk;Lee, Yang-Won;Suh, Yong-Cheol
    • Spatial Information Research
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    • v.18 no.4
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    • pp.141-149
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    • 2010
  • One of recent trends in Web-based GIS is the system development using FOSS (Free and Open Source Software). Open Source software is independent from the technologies of commercial software and can increase the reusability and extensibility of existing systems. In this study, we developed a Web-based GIS for interactive visualization of geographic information using Google Earth and spatial DBMS(database management system). Google Earth Plug-in and Google Earth API(application programming interface) were used to embed a geo-browser in the Web browser. In order to integrate the Google Earth with a spatial DBMS, we implemented a KML(Keyhole Markup Language) generator for transmitting server-side data according to user's query and converting the data to a variety of KML for geovisualization on the Web. Our prototype system was tested using time-series of LAI(leaf area index), forest map, and crop yield statistics. The demonstration included the geovisualization of raster and vector data in the form of an animated map and a 3-D choropleth map. We anticipate our KML generator and system framework will be extended to a more comprehensive geospatial analysis system on the Web.

Development of a Framework for Evaluating Time Domain Performance of a Floating Offshore Structure with Dynamic Positioning System (동적위치유지시스템을 이용하는 부유식 해양구조물의 시간대역 성능평가를 위한 프레임워크의 개발)

  • Lee, Jaeyong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.11
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    • pp.718-724
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    • 2017
  • Considerable efforts have been made to expand the boundaries of domestic offshore plant industries, which have focused on the construction of the structures, to the engineering field. On the other hand, time domain analysis, which is one of the most important areas in designing floating offshore plants, relies mainly on the information given by foreign companies. As an early design of the Dynamic Positioning System (DPS) is mostly conducted by several specialized companies, domestic ship builders need to spend time and money to reflect the analysis into the hull shape design. This paper presents the framework required to analyze time domain performance of floating type offshore structures, which are equipped with DPS. To easily perform time domain analysis, framework generates the required input data for the solver, and is modularized to test the control algorithm and performance of a certain DPS. The effectiveness of the developed framework was verified by a simulation with a model ship and the total time for the entire analysis work was reduced by 50% or more.

SQL Based Persistence Framework (구조화질의언어 기반 퍼시스턴스 프레임워크)

  • Cho, Dong-il;Rhew, Sung-Yul
    • Annual Conference of KIPS
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    • 2007.11a
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    • pp.463-466
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    • 2007
  • 웹기반 기업형 어플리케이션은 객체지향 언어로 개발되고, 데이터의 관리는 RDB(Relational Database)를 이용하여 구축된다. 두 시스템은 이질적 패러다임에 기인하여 모델의 불일치성(object-relational impedance mismatch)을 발생시킨다. 이 문제를 해결하고자 사용되는 객체-관계 매핑 프레임워크(ORM-Framework)는 RDB 의 테이블과 객체지향 언어의 객체를 매핑하는 구조로 복잡한 메타정보를 이용하여 동적으로 매핑하기 때문에 개발이 복잡하고, 변경에 유연하지 못하여 유지보수에 많은 어려움이 있다. 본 논문에서는 기존 ORM 프레임웍크의 복잡성을 해소하고, 변경에 유연한 퍼시스턴스 프레임워크를 제안한다. 제안되는 프레임워크는 SQL 을 래핑하는 구조로 테이블과 객체의 메타정보가 불필요하고, 정형화된 구조를 가진 래퍼의 사용으로 소스코드를 자동 생성하여 개발 및 유지보수의 편의성을 제공하고, 변경에 유연하다. 제안 프레임워크는 Hibernate, iBATIS 와의 테스트 결과 구동 매커니즘이 거의 동일한 iBATIS 와는 처리속도가 비슷했고, Hibernate 의 약 3 배 빠른 속도를 보였다. 코딩량은 Hibernate 대비 1/9, iBATIS 대비 1/4 을 나타냈다.

Semantics-Preserving Mutation-Based Fuzzing on JavaScript Interpreters (자바스크립트 엔진에 대한 시맨틱 보존적 변이기반 퍼징)

  • Oh, DongHyeon;Choi, JaeSeung;Cha, SangKil
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.4
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    • pp.573-582
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    • 2020
  • Fuzzing is a method of testing software by randomly generating test cases. Since its introduction, a variety of fuzzing techniques have been studied. Among them, mutation-based fuzzing is an efficient method that finds real-world bugs even though it uses a simple approach such as probabilistic bit-flipping and character substitution. However, the interpreter fuzzing has difficulty in applying general mutation techniques because the interpreter requires grammar and semantic correctness input values. In this paper, we present a novel mutation-based fuzzing on JavaScript interpreters with a dynamic data flow analysis. To this end, we implement JMFuzzer that can generate various types of mutated test cases that operate normally without runtime errors in JavaScript interpreter considering syntax and semantics. As a result, we found numerous unknown vulnerabilities in the latest JavaScript interpreters. We reported all of them to the vendors.

Tracking Method of Dynamic Smoke based on U-net (U-net기반 동적 연기 탐지 기법)

  • Gwak, Kyung-Min;Rho, Young J.
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.4
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    • pp.81-87
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    • 2021
  • Artificial intelligence technology is developing as it enters the fourth industrial revolution. Active researches are going on; visual-based models using CNNs. U-net is one of the visual-based models. It has shown strong performance for semantic segmentation. Although various U-net studies have been conducted, studies on tracking objects with unclear outlines such as gases and smokes are still insufficient. We conducted a U-net study to tackle this limitation. In this paper, we describe how 3D cameras are used to collect data. The data are organized into learning and test sets. This paper also describes how U-net is applied and how the results is validated.