• Title/Summary/Keyword: 범죄화 분석

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역추적 기술 및 보안 요구사항 분석

  • Han, Jung-Hwa;Kim, Rach-Hyun;Ryou, Jae-Cheol;Youm, Heung-Youl
    • Review of KIISC
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    • v.18 no.5
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    • pp.132-141
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    • 2008
  • 최근 인터넷의 급속한 발전을 기반으로 국경을 초월하여 인터넷을 이용한 각종 해킹, 사이버 공격 및 범죄가 기하급수적으로 증가하고 있다. 이와 같은 상황에서 각종 침해사고로부터 시스템, 네트워크 및 중요한 정보를 보호하기 위한 다양한 보안 강화 시스템이 개발되어 적용 운용되고 있지만, 현재 적용되어 사용되고 있는 보안 강화 시스템들은 해킹, 공격 및 범죄가 발생된 후 이를 막기 위한 방법으로 수동적인 기능으로 사용되고 있다. 그 결과 해킹, 사이버 공격 및 범죄를 사전에 미리 방지하는 데는 한계를 갖고 있는 것이 사실이다. 때문에, 현재 역추적 분야에서는 해킹, 사이버 공격 및 범죄가 발생할 경우 능동적이고 실시간으로 빠른 추적이 가능한 보안 강화 시스템을 목표로 하는 연구가 진행되고 있다. 이에 본 논문에서는 TCP/IP 기반의 다양한 역추적 기술을 각각 분석하고 역추적 기술을 발전시키기 위한 요구사항을 분석하여 연구동향에 관하여 살펴보고자 한다. 본 논문은 참고문헌 [16]의 결과를 활용해 작성했으나, 표준화 동향과 요구사항, 요구사항에 근거한 기존 방식들의 특징을 제시하였다.

Designing SMS Phishing Profiling Model (스미싱 범죄 프로파일링 모델 설계)

  • Jeong, Youngho;Lee, Kukheon;Lee, Sangjin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.2
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    • pp.293-302
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    • 2015
  • With the attack information collected during SMS phishing investigation, this paper will propose SMS phishing profiling model applying criminal profiling. Law enforcement agencies have used signature analysis by apk file hash and analysis of C&C IP address inserted in the malware. However, recently law enforcement agencies are facing the challenges such as signature diversification or code obfuscation. In order to overcome these problems, this paper examined 169 criminal cases and found out that 89% of serial number in cert.rsa and 80% of permission file was reused in different cases. Therefore, the proposed SMS phishing profiling model is mainly based on signature serial number and permission file hash. In addition, this model complements the conventional file hash clustering method and uses code similarity verification to ensure reliability.

Investigation of Cryptocurrency Crimes Using Open Source Intelligence (OSINT): focused on Integrated Techniques with Methods and Framework (공개출처정보(OSINT)를 활용한 가상화폐 범죄 추적 분석 기법: 방법(Methods) 및 프레임워크(Framework)의 통합 적용)

  • Byung Wan Suh;Won-Woong Kim
    • Convergence Security Journal
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    • v.24 no.3
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    • pp.23-31
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    • 2024
  • The anonymity and decentralized nature of cryptocurrencies make them highly susceptible to criminal exploitation, requiring the development of effective tracking techniques. By analyzing various open source intelligence(OSINT), such as public data, social media, and online forums, open source intelligence can provide useful information for identifying criminals and tracking the flow of cryptocurrency funds. In this study, we present a comprehensive proposal for the utilization of open source intelligence. We will discuss the current status and trends of cryptocurrency and related crimes, and introduce the concept and methodology of open source intelligence. The paper then focuses on five methods and seven frameworks of open source intelligence for tracking and analyzing cryptocurrency-related crimes, and presents techniques for the integrated application of open source intelligence methods and frameworks.

Base Location Prediction Algorithm of Serial Crimes based on the Spatio-Temporal Analysis (시공간 분석 기반 연쇄 범죄 거점 위치 예측 알고리즘)

  • Hong, Dong-Suk;Kim, Joung-Joon;Kang, Hong-Koo;Lee, Ki-Young;Seo, Jong-Soo;Han, Ki-Joon
    • Journal of Korea Spatial Information System Society
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    • v.10 no.2
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    • pp.63-79
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    • 2008
  • With the recent development of advanced GIS and complex spatial analysis technologies, the more sophisticated technologies are being required to support the advanced knowledge for solving geographical or spatial problems in various decision support systems. In addition, necessity for research on scientific crime investigation and forensic science is increasing particularly at law enforcement agencies and investigation institutions for efficient investigation and the prevention of crimes. There are active researches on geographic profiling to predict the base location such as criminals' residence by analyzing the spatial patterns of serial crimes. However, as previous researches on geographic profiling use simply statistical methods for spatial pattern analysis and do not apply a variety of spatial and temporal analysis technologies on serial crimes, they have the low prediction accuracy. Therefore, this paper identifies the typology the spatio-temporal patterns of serial crimes according to spatial distribution of crime sites and temporal distribution on occurrence of crimes and proposes STA-BLP(Spatio-Temporal Analysis based Base Location Prediction) algorithm which predicts the base location of serial crimes more accurately based on the patterns. STA-BLP improves the prediction accuracy by considering of the anisotropic pattern of serial crimes committed by criminals who prefer specific directions on a crime trip and the learning effect of criminals through repeated movement along the same route. In addition, it can predict base location more accurately in the serial crimes from multiple bases with the local prediction for some crime sites included in a cluster and the global prediction for all crime sites. Through a variety of experiments, we proved the superiority of the STA-BLP by comparing it with previous algorithms in terms of prediction accuracy.

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Visualized Determination for Installation Location of Monitoring Devices using CPTED (CPTED기법을 통한 모니터링 시스템 설치위치 시각화 결정법)

  • Kim, Joohwan;Nam, Doohee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.15 no.2
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    • pp.145-150
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    • 2015
  • Needs about safety of residents are important in urbanized society, elderly and small-size family. People are looking for safety information system and device of CPTED. That is, Needs and Installations of CCTV increased steadily. But, scientific analysis about validity, systematic plan and location of security CCTV is nonexistent. It is simply put these devised in more demanded areas. It has limits to look for safety of residents by increasing density of CCTVs. One of the characteristics of crime is clustering and stong interconnectivity. So, exploratory spatial data of crime is geo-coded using 2 years data and carried out cluster analysis and space statistical analysis through GIS space analysis by dividing 18 variables into social economy, urban space, crime prevention facility and crime occurrence index. The result of analysis shows cluster of 5 major crimes, theft, violence and sexual violence by Nearest Neighbor distance analysis and Ripley's K function. It also shows strong crime interconnectivity through criminal correlation analysis. In case of finding criminal cluster, you can find criminal hotspot. So, in this study I found concept of hotspot and considered technique about selection of hotspot. And then, selected hotspot about 5 major crimes, theft, violence and sexual violence through Nearest Neighbor Hierarchical Spatial Clustering.

Application of Crime Prevention Design based on Public Data Analysis: Focusing on Seoul (공공데이터분석 기반 범죄예방환경설계 적용 : 서울시 중심으로)

  • Kim, Sung-Jun
    • Korean Security Journal
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    • no.60
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    • pp.91-111
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    • 2019
  • Violent crimes have increased continuously due to the development of urban society and have become a threatening factor against the residential safety of citizens. The prevention of these crimes is always a major topic in human society and one of the fundamental elements of the quality of life and safety of citizens. In recent years, much attention has been paid to environmental design through the Crime Prevention Through Environmental Design (CPTED) as a preventive measure. Currently, South Korea is promoting the openness and utilization of public data, and crime prevention is one of the fields that can utilize public data actively. This approach to crime prevention utilizing public data will be helpful for the proposal of policies from new viewpoints departing from the general utilization measures of CPTED that improve streetlights and closed-circuit television (CCTV) installations, whose limitations have been pointed out as they are only mechanical surveillance. Thus, this study sets the research scope based on the statistics of the status of five criminal offenses by administrative district in recent years provided by the data portal in Seoul City, the capital of South Korea, as the utilization data and concentrates on the analysis. Based on the analysis results, this study proposes a method to utilize classical music as a new policy for regions where the improvements are most needed. The open-source Python analysis program was employed as the main data analysis and visualization method.

Design and Implementation of Crime Prevention System Targeting Women by Using Public BigData (공공 빅데이터를 이용한 여성 대상 범죄 예방 시스템의 설계 및 구현)

  • Ko, Sung-Wook;Oh, Su-Bin;Baek, Se-In;Park, Hyeok-Ju;Park, Mee-Hwa;Lee, Kang-Woo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.561-564
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    • 2016
  • If using crime map which represents criminal section that violent crimes targeting women frequently happened, the police could prevent additional crimes by positioning themselves intensively in expected crime zones and each individual could avoid being damaged by referring information of criminal zones. In this paper, by analyzing crimes targeting women and offender information which is provided in public-opened datum portal, we suppose a system which prevents crimes that calculates locational danger and, by considering location and age group of users, provides user-customized information of danger. By crawling the criminals datum which is provided in public-opened datum portal, It collects them. About the areas which happened sexual crimes, calculating danger of crime based on statistical crime information including criminal information, residence of offenders, areas which happened sexual crimes, sentences and the number of crime, this system is able to visualize the areas which sexual crimes happened based on information of danger grade representing on user's location. The score of danger calculated in location unit can provide criminal information according to location and ages of users by interacting GIS.

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A Study on Elements of Crime Facts and Visualizing the Storyline through Named Entity Recognition and Event Extraction (개체명 인식과 이벤트 추출을 통한 판결문 범죄사실 구성요소 및 스토리라인 시각화방안 연구)

  • Lee, Yu-Na;Park, Sung-Mi;Park, Ro-Seop
    • Annual Conference of KIPS
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    • 2022.11a
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    • pp.490-492
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    • 2022
  • 최근 사법분야에 지능형 법률 서비스를 제공하게 되면서 학습데이터로서 판결문의 중요성이 높아지고 있다. 그중 범죄사실은 수사자료와 유사하여 범죄수사에 귀중한 자료역할을 하고 있지만, 주체가 생략되거나 긴 문장의 형태로 인해 구성요건을 추출하고 사건의 인과관계 파악이 어려울 수 있어 이를 분석하는데 적지 않은 시간과 인력이 소비될 수밖에 없다. 따라서, 본 논문에서는 사전학습모델을 활용한 개체명 인식과 형태소 분석기반 이벤트 추출기법을 범죄사건 재구성에 적용하여 핵심 사건추출을 간편화하고 시각적으로 표현해 전체적인 사건 흐름 이해도를 향상할 수 있는 방법론을 제안하고자 한다.

Prediction of the Number of Crimes according to Urban Environmental Factors in the Metropolitan Area (수도권 도시 환경 요인에 따른 범죄 발생 건수 예측)

  • Ye-Won Jang;Ye-Lim Kim;Si-Hyeon Park;Jae-Young Lee;Yoo-Jin Moon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.321-322
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    • 2023
  • 본 논문에서는 Scikit-learn 패키지의 LinearRegression 모델과 Keras 딥러닝 모델을 활용하여 수도권 도시 환경 요인에 따른 범죄 발생 건수를 예측 모델을 제안한다. 연구 방법으로 범죄 발생과 유의미한 관계가 있다고 파악되는 수도권의 각 자치구 별 데이터셋을 분석하여, CCTV, 파출소, 가로등의 수가 범죄 발생에 유의미한 영향을 끼치는 것을 확인하였다. 독립 변수들 간에 Scale을 줄이고자 정규화를 진행했고, 종속변수의 정규성 확보를 위해 로그변환을 취했다. 손실 함수는 회귀문제에서 사용되는 'relu'함수를 사용했고 모델의 성능을 확인할 수 있는 지표로 MSE(Mean Squared Error)를 사용해 모델을 구성하였다. 본 논문에서 설계한 이 프로그램은 범죄 발생율이 높은 지역구에 경찰 인력의 추가적 배치, 안전 시설 확충 등 실무적 조치를 취함에 있어 근거를 제공할 수 있을 것으로 사료된다.

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Spatial Analysis of the Difference between Real Crime and Fear of Crime (도시내 범죄발생과 범죄 두려움 위치의 공간적 차이 분석)

  • Heo, Sun-Young;Moon, Tae-Heon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.14 no.4
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    • pp.194-207
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    • 2011
  • This study tries to find the possibility to prevent crime by improving urban spatial environment through the analysis of spatial environment property that mutually coincides or differs by comparing the place where crime actually occurs and the place where citizen is afraid of crime. The method of study is as follows. First, the ontents scope and method of study was established by theoretic investigation of case study related to crime. Second, as crime cannot be prevented by police power only, CPSCP(Citizen Participation System for Crime Prevention) was developed so that all citizen can cooperatively participate in the crime prevention anytime and anywhere. Third, the data on the place where people feel fear in the region was collected by directly indicating the place where citizen is afraid of crime in the space by utilizing CPSCP. Fourth, the place where crime actually occurs and the place where citizen is afraid of crime are redundantly analyzed for comparative analysis of 2 places. The result shows that environmental design improving physical environment of urban space is necessary to prevent crime and to eliminate the fear of crime. The CPSCP developed by this study which will be advanced to U-crime prevention system will contribute to making citizen's own neighborhood a smart safety city autonomously.