• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.161-171
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• 2018

This study set out to identify crime vulnerable areas with the GIS spatial analysis technique for the prediction of crimes. Crime vulnerable areas were extracted from the statistics of crimes with the GIS hotspot analysis technique and the inverse distance weighted(IDW) method applied to different crimes according to places and use districts. The scope of surveillance and weight were calculated for each of CPTED surveillance elements including CCTV, streetlamp, patrol division, and police substation. Maps of crime vulnerable areas were overlapped one after another to make a CPTED-based one expressed in four grades(safety, attention, warning, and risk).

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.451-459
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• 2017

This study reviewed literatures on crime victim support in Korea. KERIS, KISS and NANET were searched with "Victims of Crime Support" as keywords. In result, 314 were satisfied the eligible criteria for the review. The number of articles have steadily increased especially after the related law & policy were announced and after the outbreak of violent crimes. Among the research methods, qualitative studies appeared the most. Regarding the research topics, articles related to implementation of the law and policy ranked the highest in number. Among the type of crimes the number of sexual and domestic violence were reported the most. The number of studies on children and adolescent was shown with the highest frequency in minor groups. Finally, the psychological support appeared relatively low. This study suggests more empirical studies on psychological support for crime victims need to be administered as its future direction.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.75-80
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• 2020

Since the Fourth Industrial Revolution, important technologies such as big data analysis, robotics, Internet of Things, and the artificial intelligence have been used in various fields. Generally speaking it is understood that the big-data technology consists of gathering stage for enormous data, analyzing and processing stage and distributing stage. Until now crime records which is one of useful big-sized data are utilized to obtain investigation information after occurring crimes. If crime records are utilized to predict crimes it is believed that crime occurring frequency can be lowered by processing big-sized crime records in big-data framework. In this research the design is proposed that the smart system can provide the users of smart devices crime occurrence probability by processing crime records in big-data analysis. Specifically it is meant that the proposed system will guide safer routes by displaying crime occurrence probabilities on the digital map in a smart device. In the experiment result for a smart application dealing with small local area it is showed that its usefulness is quite good in crime prevention.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.57-62
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• 2014

In this paper, we proposed and implemented a crime pattern analysis algorithm using big data. The proposed algorithm uses crime-related big data collected and published in the supreme prosecutors' office. The algorithm analyzed crime patterns in Seoul city from 2011 to 2013 using the spatial statistics analysis like the standard deviational ellipse and spatial density analysis. Using crime frequency, We calculated the crime probability and danger factors of crime areas, time, date, and places. Through a result we analyzed spatial statistics. As the result of the proposed algorithm, we could grasp differences in crime patterns of Seoul city, and we calculated degree of risk through analysis of crime pattern and danger factor.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.71-77
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• 2014

People in the modern society want to live under safe and comfortable circumstances. As our society, however, is sharply developing, crimes are getting smarter and more difficult to treat. Above all, they often take place around us, and we are trying to cope with them variously in order to make our lives more comfortable and safer. In particular, five major crimes(Murde, Robber, Rape, Violence, Theft ) that most frequently occur in the real life are very threatening and fearful so it is necessary to deal with them with "the scientific method." In this study, therefore, we searched the frequency of crime by its type and analyzed spatial characteristics between crimes and criminal factors by using regression analysis and correlation analysis based on the crime data that has occurred around Geumjeng-gu, Busan so that we can confront five major crimes.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.6-11
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• 2015

In this paper, we analyzed current states and spatial characteristics of crime occurring in A city of Colombia using big data of crime. The analysis draws on the crime statistics of Colombia National Police Agency from 2013 January to September. We also investigated spatial autocorrelation of crime using global and local Moran's Index. Spatial autocorrelation analysis shows significant spatial autocorrelation in the high frequency of crime. Global Moran's I analysis indicates that there are statistically significant value of crime area. Using local Moran's Index analysis, we also implement Local Indicators of Spatial Association(LISA) map and hot spot analysis helps us identify crime distribution.

• The Korean Journal of Applied Statistics
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• v.12 no.2
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• pp.657-670
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• 1999

공공기관에서 발간하는 공식통계자료들을 살펴보면 대부분 관찰값으로 총 빈도수나 또는 전체를 기준으로 하여 그 빈도수가 차지하는 퍼센트 그리고 지수 등으로 나타나 있다. 이러한 자료는 단순히 공무원들에게 행정용으로 활용되고는 있으나 일반인들이 자료를 이해하고 나아가 활용하기는 어렵다. 이런 자료들이 일반인을 위한 자료가 되기 위해서는 국민 한사람(또는 기본 단위)당 그 발생 확률을 구하여 제시하고 나아가 개개인의 여러 복잡한 현실 상황을 고려해도 그 확률 계산이 용이하도록 기초적인 자료를 제공하는 것이 바람직하다고 사료된다. 즉, 육하(六河)원칙을 근거로한 현상에 대하여 확률을 구하고 활용할 수 있는 방안을 제시한다. 이 논문에서는 경찰청에서 발표된 교통사고에 대한 통계자료와 대검찰청에서 발표된 범죄사건 통계자료를 통계학의 기본인 확률의 개념을 도입하여 보다 이해가 쉽고, 나아가 교통사고와 범죄 피해를 최소한으로 줄일수 있는 자료로 변환하여 설명하고자 한다.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.93-101
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• 2015

In modern society, various crimes is occurred. It is necessary to predict the criminal in order to prevent crimes, various studies on the prediction of crime is in progress. Crime-related data, is announced to the statistical processing of once a year from the Public Prosecutor's Office. However, relative to the current point in time, data that has been statistical processing is a data of about two years ago. It does not fit to the data of the crime currently being generated. In This paper, crime prediction data was apply with Naver trend data. By using the Web traffic Naver trend, it is possible to obtain the data of interest level for crime currently being generated. It was constructed a modeling that can predict the crime by using traffic data of the Naver web search. There have been applied to Markov chains prediction theory. Among various crimes, murder, arson, rape, predictive modeling was applied to target. And the result of predictive modeling value was analyzed. As a result, it got the same results within 20%, based on the value of crime that actually occurred. In the future, it plan to advance research for the predictive modeling of crime that takes into the characteristics of the season.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.20-29
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• 2021

This study aims to explore the issue of drones and crime in newspaper articles. BIG KINDS, an online news archive of the Korea Press Foundation, collected 1,213 newspaper articles that met the terms of "drone" and "crime" in 11 central and 28 regional comprehensive newspapers between January 1, 1990 and May 1, 2021. Among them, we perform keyword frequency, centrality analysis, network structure construction, CONCOR analysis, and density matrix analysis on 117 key keywords. According to the analysis, the main issues were classified into eight, and the report analysis on drones and crimes in newspaper articles showed that the government's policy-making and social problems on protecting people's privacy, preventing illegal filming, securing navigation safety, social security and resolution. This study attempts to expand the field of humanities and social studies related to drones and crime, and specifically suggests the current status and counterplan against drone-related crimes as policy implications and media implications.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.107-116
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• 2012

In this paper we propose a method that can generate the risk probability map in the form of raster shape by using Markov Chain methodology applied to the object interpretation keys and quantified risk indexes. These object interpretation keys, which are primarily characteristics that can be identified by the naked eye, are set based on the objects that comprise the spatial information of a certain urban area. Each key is divided into a cell, and then is weighted by its own risk index. These keys in turn are used to generate the unified risk probability map using various levels of crime prediction probability maps. The risk probability map may vary over time and means of applying different sets of object interpretation keys. Therefore, this method can be used to prevent crimes by providing the ways of setting up the best possible police patrol beat as well as the optimal arrangement of surveillance equipments.