• Title/Summary/Keyword: 고유식별정보

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Dynamic Warping Based Iris Recognition Method by Considering Non-Linear Scaling Characteristic of Iris Muscle (홍채 근육의 비선형적 스케일링 특성을 고려한 Dynamic Warping 기반 홍채인식 방법)

  • Bae, Min-Kyoung;Han, Hyuk Soo;Lee, Eui Chul
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.10a
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    • pp.1467-1469
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    • 2015
  • 일반적인 홍채 인식 방법은 홍채 근육이 형성하는 고유 패턴에 기초하여 사용자를 식별한다. 홍채의 주요 기능은 자연광의 양에 따라 동공의 크기를 제어하는 것이다. 그러므로 홍채 패턴은 조명 조건의 변화에 따라 팽창 및 수축한다. 홍채 패턴의 변형에도 불구하고 강력한 인식의 정확도를 보장하기 위해 이전의 연구에서는 홍채 근육은 선형적으로 변형된다고 가정하여, 홍채의 트랙을 선형적이고 균일하게 할당하였다. 그러나 홍채 패턴은 실제로 특정 홍채 근육의 복잡한 움직임으로 인해 비선형적으로 변형된다. 이러한 문제점을 극복하기 위해 Dynamic Warping 방법을 사용하여 비선형성을 고려한 새로운 매칭 방법을 제안한다.

The attacker group feature extraction framework : Authorship Clustering based on Genetic Algorithm for Malware Authorship Group Identification (공격자 그룹 특징 추출 프레임워크 : 악성코드 저자 그룹 식별을 위한 유전 알고리즘 기반 저자 클러스터링)

  • Shin, Gun-Yoon;Kim, Dong-Wook;Han, Myung-Mook
    • Journal of Internet Computing and Services
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    • v.21 no.2
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    • pp.1-8
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    • 2020
  • Recently, the number of APT(Advanced Persistent Threats) attack using malware has been increasing, and research is underway to prevent and detect them. While it is important to detect and block attacks before they occur, it is also important to make an effective response through an accurate analysis for attack case and attack type, these respond which can be determined by analyzing the attack group of such attacks. Therefore, this paper propose a framework based on genetic algorithm for analyzing malware and understanding attacker group's features. The framework uses decompiler and disassembler to extract related code in collected malware, and analyzes information related to author through code analysis. Malware has unique characteristics that only it has, which can be said to be features that can identify the author or attacker groups of that malware. So, we select specific features only having attack group among the various features extracted from binary and source code through the authorship clustering method, and apply genetic algorithm to accurate clustering to infer specific features. Also, we find features which based on characteristics each group of malware authors has that can express each group, and create profiles to verify that the group of authors is correctly clustered. In this paper, we do experiment about author classification using genetic algorithm and finding specific features to express author characteristic. In experiment result, we identified an author classification accuracy of 86% and selected features to be used for authorship analysis among the information extracted through genetic algorithm.

Analysis of Target Identification Performances Using Bistatic ISAR Images (바이스태틱 ISAR 영상을 이용한 표적식별 성능 분석)

  • Lee, Seung-Jae;Lee, Seong-Hyeon;Kang, Min-Seok;Yang, Eunjung;Kim, Kyung-Tae
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.27 no.6
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    • pp.566-576
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    • 2016
  • Inverse synthetic aperture radar(ISAR) image generated from bistatic radar(Bi-ISAR) represents two-dimensional scattering distribution of a target, and the Bi-ISAR can be used for bistatic target identification. However, Bi-ISAR has large variability in scattering mechanisms depending on bistatic configurations and do not represent exact range-Doppler information of a target due to inherent distortion. Thus, an efficient training DB construction is the most important factor in target identification using Bi-ISARs. Recently, a database construction method based on realistic flight scenarios of a target, which provides a reliable identification performance for the monostatic target identification, was applied to target identification using high resolution range profiles(HRRPs) generated from bistatic radar(Bi-HRRPs), to construct efficient training DB under bistatic configurations. Consequently, high identification performance was achieved using only small amount of training Bi-HRRPs, when the target is a considerable distance away from the bistatic radar. Thus, flight scenarios based training DB construction is applied to target identification using Bi-ISARs. Then, the capability and efficiency of the method is analyzed.

Analysis of Target Identification Performances against the Moving Targets Using a Bistatic Radar (바이스태틱 레이다를 이용한 이동표적에 대한 표적식별 성능 분석)

  • Lee, Seung-Jae;Bae, Ji-Hoon;Jeong, Seong-Jae;Yang, Eunjung;Kim, Kyung-Tae
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.27 no.2
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    • pp.198-207
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    • 2016
  • Bistatric radar can perform detection and identification for stealth targets that are rarely detected by the conventional monostatic radar. However, high resolution range profile(HRRP) generated from the received signal in the bistatic radar cannot show exact range information of the target because the bistatic geometry lead to the distortions of the bistatic HRRP. In addition, electromagnetic scattering mechanisms of the target are varied depending on the bistatic geometry. Thus, efficient database construction is a crucial factor to achieve successful classification capability in bistatic target identification. In this paper, a database construction method based on realistic flight scenarios of a target, which provides a reliable identification performance for the monostatic radar, is applied to bistatic target identification. Then, the capability and efficiency of the method is analyzed. Simulation results show that reliable identification performance can be achieved using the database construction based on the flight scenarios when the target is a considerable distance away from the bistatic radar.

A Study on Similarity Comparison for Detecting Theft of Android Application (안드로이드 앱 도용 탐지를 위한 유사도 비교 연구)

  • Park, Seik;Park, Heekwang;Choi, Sungha;Park, Heewan
    • Proceedings of the Korea Information Processing Society Conference
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    • 2011.11a
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    • pp.868-871
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    • 2011
  • 소프트웨어 버스마크는 모든 프로그램에 이미 포함되어 있으며 서로 다른 프로그램을 식별하는데 사용될 수 있는 프로그램의 고유한 특징을 말한다. 본 논문에서는 소프트웨어 버스마크를 이용하여 안드로이드 앱 사이의 유사도를 측정하고 코드 도용 탐지에 활용하는 방법을 제안하였고, 다양한 카테고리의 안드로이드 앱에 대한 유사도 비교 실험을 하였다. 먼저, 같은 개발사에서 만든 유사한 프로그램을 대상으로 버스마크 유사도를 측정한 결과 유사도가 매우 높다는 것을 확인하였다. 또한, 서로 다른 개발사에서 만든 유사한 카테고리의 프로그램을 비교하였고 비슷한 프로그램이라도 서로 다른 개발사에서 만든 앱이기 때문에 유사도가 낮다는 것을 확인하였다. 마지막으로, 서로 다른 개발사의 유사한 프로그램들 중에서 유사도가 높게 측정된 경우를 탐지한 실험 결과를 제시하였다. 이러한 유사 앱들은 실제로 공통 클래스를 함께 포함하고 있었다. 실험 결과들을 바탕으로 소프트웨어 버스마크가 안드로이드 앱 사이의 공통 클래스를 탐지하는데 활용될 수 있음을 확인하였고, 더 나아가 안드로이드 앱에서의 코드 도용을 탐지하는 목적으로도 활용될 수 있음을 보여주었다.

Test of Fault Detection to Solar-Light Module Using UAV Based Thermal Infrared Camera (UAV 기반 열적외선 카메라를 이용한 태양광 모듈 고장진단 실험)

  • LEE, Geun-Sang;LEE, Jong-Jo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.4
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    • pp.106-117
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    • 2016
  • Recently, solar power plants have spread widely as part of the transition to greater environmental protection and renewable energy. Therefore, regular solar plant inspection is necessary to efficiently manage solar-light modules. This study implemented a test that can detect solar-light module faults using an UAV based thermal infrared camera and GIS spatial analysis. First, images were taken using fixed UAV and an RGB camera, then orthomosaic images were created using Pix4D SW. We constructed solar-light module layers from the orthomosaic images and inputted the module layer code. Rubber covers were installed in the solar-light module to detect solar-light module faults. The mean temperature of each solar-light module can be calculated using the Zonalmean function based on temperature information from the UAV thermal camera and solar-light module layer. Finally, locations of solar-light modules of more than $37^{\circ}C$ and those with rubber covers can be extracted automatically using GIS spatial analysis and analyzed specifically using the solar-light module's identifying code.

Social Network Spam Detection using Recursive Structure Features (소셜 네트워크 상에서의 재귀적 네트워크 구조 특성을 활용한 스팸탐지 기법)

  • Jang, Boyeon;Jeong, Sihyun;Kim, Chongkwon
    • Journal of KIISE
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    • v.44 no.11
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    • pp.1231-1235
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    • 2017
  • Given the network structure in online social network, it is important to determine a way to distinguish spam accounts from the network features. In online social network, the service provider attempts to detect social spamming to maintain their service quality. However the spammer group changes their strategies to avoid being detected. Even though the spammer attempts to act as legitimate users, certain distinguishable structural features are not easily changed. In this paper, we investigate a way to generate meaningful network structure features, and suggest spammer detection method using recursive structural features. From a result of real-world dataset experiment, we found that the proposed algorithm could improve the classification performance by about 8%.

Development of a Supporting Tool for Conceptual Component Modeling and Component Construction on the J2EE Platform (J2EE 플랫폼에서의 개념적 컴포넌트 모델링 및 컴포넌트 생성 지원 도구 개발)

  • Lee, U-Jin;Kim, Min-Jeong;Jeong, Yang-Jae;Yun, Seok-Jin;Choe, Yeon-Jun
    • The KIPS Transactions:PartD
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    • v.8D no.6
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    • pp.761-770
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    • 2001
  • As software industry is rapidly evolving, IT business enterprises have been meeting with cutthroat competition in developing software. As software reusability, time to market, and maintainability are considered as a competitive edge, software component techniques have lately attracted considerable attention. Currently, although there are some supporting tools for developing software components, they do not have tight connections among component developing processes such as component identification, component modeling, detailed design, code generation, deployment, and testing. And it is restrictive for users to construct various scales of components on component platform architecture. In this paper, we provide an implementation and a design of a supporting tool for constructing platform-independent software components, which covers all development lifecycles of components. In the phase of component modeling, platform independent, conceptual components are identified from domain model information in the view of system partitioning. Detailed design and implementation of a component are performed on the J2EE platform architecture. And the changes on the design model and source codes are consistently managed by using round-trip techniques.

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Extending Bibliographic Information Using Linked Data (링크드 데이터 방식을 통한 서지 정보의 확장에 관한 연구)

  • Park, Zi-Young
    • Journal of the Korean Society for information Management
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    • v.29 no.1
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    • pp.231-251
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    • 2012
  • In this study, Linked Data was used for extending bibliographic data, because Linked Data provides shareable identifiers, data structures, and link information. Linked Data is especially efficient in expanding bibliographic data integrated with bibliographic ontology. Therefore, Linked Data and bibliographic ontologies were analyzed and available Linked Data was suggested. By linking between meta-data schemes, bibliographic data, and authority data, issues for the effective Linked Data sharing were suggested: 1) selecting proper Linked Data for each bibliographic organization, 2) linking between different Linked Data, and 3) developing their own Linked Data for each bibliographic organization.

A Study on Feature-Factors Extraction for Fingerprints Recognition (지문인식을 위한 특징요소 추출에 관한 연구)

  • Roh, Jeong-Seok;Jeong, Yong-Hoon;Choi, Young-Kyoo;Lee, June-Hwan;Rhee, Sang-Burm
    • Proceedings of the Korea Information Processing Society Conference
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    • 2003.05a
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    • pp.687-690
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    • 2003
  • 지식 정보화 시대에 들어서면서부터 정보는 개인이나 일부 기관에 국한됨이 없이 중요시되고 있지만, 그 경계는 나날이 모호해지고 정보의 양은 급속하게 늘어가고 있는 것이 오늘날의 현실이다. 이러한 시대적 환경은 보안의 중요성이 크게 부각되어 생체인식 기술에 대한 관심을 높아지게 만들었다. 생체인식(Biometrics)분야 중에서도 지문 인식(Recognition)은 많은 연구가 이루어졌으나 개선할 점이 여전히 남아있다. 특히, 정확성 및 속도향상이라는 측면이 그렇다고 할 수 있겠다. 본 논문에서는 기존의 지문 인증(Authentication)시스템의 지문 영상(Image)의 식별 능력을 증가시키고 다수의 지문 영상에서도 좋은 결과를 가져올 수 있는 고유한 특징이 될 수 있는 요소들(Factor)을 추출하여 진보된 지문인식 시스템을 구현하는 것을 궁극적인 목표로 하고 있다. 따라서, 지금까지의 관련 연구를 바탕으로 지문 인식 시스템을 구현하는 것을 궁극적인 목표로 하고 있다. 따라서. 지금까지의 관련 연구를 바탕으로 지문 인식 시스템의 성능 향상을 위해서 핵심적인 minutiae reference point, 방향 정보의 추출 방법을 제안하고 인식의 종결부라고 할 수 있는 정합(matching)에 관에서 논한 다음, 마지막으로 결론 및 향후 과제로서 개선할 부분을 제시한다.

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