• Journal of the Korea Society of Computer and Information
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• v.22 no.1
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• pp.41-48
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• 2017

In this study, we proposed GIS-based Regional Crime Prevention Index (RCPI) development method designed to support local governments with systematic crime prevention activities. The public interest in safe urban environment is increasing rapidly. The government is putting efforts into crime prevention activities to eliminate the criminal opportunities in advance. CPTED is method to prevent crimes in the city by improving environmental factors that cause crime. It is used by local governments to promote the crime prevention activities centering on the expansion of CCTVs and street lamps and the improvement of street environment. However, most policies were terminated as one-off programs and it is necessary to monitor the effect of such policies on a continuous basis. In order to alleviate issues, this study proposed RCPI as part of crime safety assessment in urban environments. The estimation of RCPI in City A of Gyeonggi-do showed relative differences in 31 districts (dong), indicating that it is also possible to evaluate the crime safety in the local community on the level of the administrative dong, the smallest administrative district in the urban environments. As a crime map, the RCPI will be used effectively as he reference to support the decision making process for local government in the future.

• Korean Security Journal
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• no.14
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• pp.261-283
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• 2007

In recent studies for explaining the causation of crime fear shows interest and effort in studies attempting microscopical individual level and macroscopical local level of sex, age, economic level, crime damage level and etc. However, in this study, it is considered that interest and analysis of individual on characteristics of these local level may has its difference depends on crime damage experience in the past, fragility precision of crime damage and interest on crime relating information and processed positive analysis on characteristics of individual and relation of crime fear on individual level before making an attempt of connecting microscopical level and macroscopical level. Therefore, the purpose of this study is on positive verification of how people feel about crime fear depends on individual's characteristic and also how much effect would they receive. As the result of this study, it is shown that first, population statistical characteristics that crime damage experience is statistically meaningful of its difference of each group are age, status of marriage, final education status and residential area and for the fragility precision of crime damage was sex and status of marriage and for the interest about the crime relating information has meaningful difference statistically of each group depends on sex, age, final education status, income of the house and location of residential area. Second, after processing correlation analysis on individual characteristic primary factor and crime fear, the result of 3 primary factor independent variable all shows statistically meaningful correlation with crime fear and especially fragility primary factor on crime damage showed the most high correlation with crime fear. Lastly, fragility of crime damage, interest on crime information and crime damage experience has effected as characteristics of individual and especially fragility of crime damage which the person thought to be the most fragility on crime damage out of these individual characteristic primary factor showed to have the most effecting primary factor.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.865-875
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• 2012

In this study, we identify the variables that affect the number of crime and spatial correlation in the Seoul metropolitan area, in addition, we measure the relative risk on the incidence of crime by a Poisson regression model. We suggest a statistical methodology to make a risk map for crime based on relative risk instead of the total event of crime by region using the Geographic Information System. To demonstrate the use and advantages of this methodology, this study presents an analyses of the total crime count in 25 wards in the Seoul metropolitan area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.221-229
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• 2015

The urban crimes that threat individual's safety are parts of the serious social problems. However. the information of crime in Korea has only been provided by forms of hot spots around place of crime, or forms of crime statistics without positional information. Those could not provide enough information to users in identifying the vulnerable areas for substantive crimes. Therefore, this study suggested a methodology of extraction in criminal vulnerable areas by using the spatial information, the statistical information and the public sector information. The crime vulnerable areas were extracted through the grid-based spatial analysis and the overlapping analysis from each of the information. In fact, the extracted areas were able to provide detailed vulnerability information than the traditional hot spot-based crime information. Following the study, the extracted results in crime vulnerable areas have displayed highly coincide with Korea safety map, provided by national disaster management institute, which regards to be able to provide crime risk rating in terms of administrative business in future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1687-1692
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• 2009

Cyber forensics is used the process and technology of digital forensics as a criminal investigation in cyber space. Cyber crime is classified into cyber terror and general cyber crime, and those two classes are connected with each other. The investigation of cyber terror requires high technology, system environment and experts, and general cyber crime is connected with general crime by evidence from digital data in cyber space. Accordingly, it is difficult to determine relational crime types, collect evidence and the legal admissibility of evidence. Therefore, we considered the classifications of cyber crime, the collection of evidence in cyber space and the application of laws to cyber crime. In order to efficiently investigate cyber crime, it is necessary to integrate those concepts for each cyber crime-case. In this paper, we constructed a cyber forensics domain ontology for cyber criminal investigation using the concepts, relations and properties, according to categories of cyber crime, laws, evidence, and information of criminals and crime-cases. This ontology can be used in the process of investigating of cyber crime-cases, and for data mining of cyber crime; classification, clustering, association and detection of crime types, crime cases, evidences and criminals.

• Asia pacific journal of information systems
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• v.5 no.1
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• pp.112-128
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• 1995

The information system control includes organizational structure, control mechanism, and management tools which contribute to accomplish the goals of information system: asset safeguarding, data integrity, effectiveness, and efficiency. Information system audit is the process to evaluate whether the information system accomplishs the goals. Information system auditor examine the reliability of information system control and suggest recommendations to improve the information system control. Both information system control and information system audit activities contribute to prevent and detect the computer crime for the organization. This paper proposes a causal model of information system control/audit and the perceived risk of computer crime, and tests the model using a survey on 38 financial institutions in Korea. Statistical results show that information system control and audit significantly reduce the computer crime risk perceived by the user group. The general control has a stronger impact than the application control. In addition, it turns out that the greater the deviation between the importance and the actual level of information system control is, the higher the perceived risk of computer crime is.

• Korean Security Journal
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• no.9
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• pp.27-68
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• 2005

Recently, because credit card crime using a personal credit information is increasing, professionalizing, and spreading the area, the loss occurring from credit card crime is enormous and is difficult to arrest and punish the criminals. At past, crime from forging and counterfeiting the credit card was originated by minority criminals, but at present, the types and appearance of credit card crime is very different to contrasting past crime. The numbers of people using credit card in the middle of 1990's was increasing and barometer of living conditions was evaluated by the number having credit card, therefore this bad phenomenon occurring from credit card crime was affected by abnormal consumption patterns. There is no need emphasizing the importance of personal credit card in this credit society. so, because credit card crime using personal credit card information has a bad effect, and brings the economic loss and harms to individuals, credit card company, and members joining credit card. Credit card crime using personal credit card information means the conduct using another people's credit card information(card number, expiring duration, secret number) that detected by unlawful means. And crime using dishonest means from another people's credit information is called a crime profiting money-making and a crime lending an illegal advance by making false documents. A findings on countermeasures of this study are as follows: Firstly, Diverting user's mind, improving the art of printing, and legitimating password from payment gateway was suggested. Secondly, Complementing input of password, disseminating the system of key-board protection, and promoting legitimations of immediate notification duty was suggested. Thirdly, Certificating the electronic certificates as a personal certificates, assuring the recognition by sense organ of organism, and lessening the ratio of crime occurrence, and restricting the ratio of the credit card crime was suggested.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.91-98
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• 2016

We propose a method to train a model that can predict the probability of a crime being committed. CCTV data by matching criminal events are required to train the crime prediction model. However, collecting CCTV data appropriate for training is difficult. Thus, we collected actual criminal records and converted them to an appropriate format using variables by considering a crime prediction environment and the availability of real-time data collection from CCTV. In addition, we identified new specific crime types according to the characteristics of criminal events and trained and tested the prediction model by applying neural network partial least squares for each crime type. Results show a level of predictive accuracy sufficiently significant to demonstrate the applicability of CCTV to real-time crime prediction.

• ETRI Journal
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• v.44 no.2
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• pp.208-219
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• 2022

Crime amount prediction is crucial for optimizing the police patrols' arrangement in each region of a city. First, we analyzed spatiotemporal correlations of the crime data and the relationships between crime and related auxiliary data, including points-of-interest (POI), public service complaints, and demographics. Then, we proposed a crime amount prediction model based on 2D convolution and long short-term memory neural network (2DCONV-LSTM). The proposed model captures the spatiotemporal correlations in the crime data, and the crime-related auxiliary data are used to enhance the regional spatial features. Extensive experiments on real-world datasets are conducted. Results demonstrated that capturing both temporal and spatial correlations in crime data and using auxiliary data to extract regional spatial features improve the prediction performance. In the best case scenario, the proposed model reduces the prediction error by at least 17.8% and 8.2% compared with support vector regression (SVR) and LSTM, respectively. Moreover, excessive auxiliary data reduce model performance because of the presence of redundant information.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.66-73
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• 2017

Due to the recent rapid changes in society and wide spread of information devices, diverse digital information is utilized in a variety of economic and social analysis. Information related to the crime statistics by type of crime has been used as a major factor in crime. However, statistical analysis using only the structured data has the difficulty in the investigation by providing limited information to investigators and users. In this paper, structured data and unstructured data are analyzed by applying Korean Natural Language Processing (Ko-NLP) and the Latent Semantic Analysis (LSA) technique. It will provide a crime profile optimum system that can be applied to the crime profiling system or statistical analysis.