• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.510-518
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• 2023

Purpose: This study compares and analyzes the characteristics and progress of existing voice phishing and new voice phishing to present a basic policy plan to prepare countermeasures against new voice phishing based on psychological descriptions. Method: The criminal progress and characteristics of the two were compared and analyzed through damage cases on various portal sites centered on voice phishing crime scenarios. Result: As a result of analyzing the progress of the third stage of new voice phishing, the scenario of new voice phishing that can deceive victims was written more carefully and the scope of the crime was expanded. In the crime execution stage, the victim was socially isolated, reducing the victim's judgment ability, making it more difficult for investigative agencies to investigate, and in the final stage, the continuity and expansion of criminal damage such as extortion of money and valuables are shown. Conclusion: There were differences in the target and scope of the crime and the method of the crime strategy between the two, and the possibility of damage is much greater, so a more efficient response strategy should be prepared.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.303-305
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• 2011

수많은 웹로그 히스토리의 자료에서 컴퓨터 사이버범죄에 대한 증거자료로 채택되기 위한 기술적인 웹 포렌식 자료의 추출에 사용되는 웹 포렌식 알고리즘은 필수적인 요소이다. 본 논문에서는 웹 로그 시나리오 작성을 제안하고 설계하여, 웹 포렌식을 통한 컴퓨터 사이버범죄에 대한 학문적 기술적 발전에 기여하고자 하는데 본 논문의 목적이 있다. 수많은 웹로그 자료에서 컴퓨터 사이버 범죄에 대한 증거 자료로 채택되기 위한 기술적인 웹 포렌식 자료의 추출에 사용되는 웹 로그 분석 알고리즘은 필수적인 요소이다. 본 논문에서는 웹 포렌식 알고리즘을 제안하고 설계하여, 실제 기업의 웹 서버 시스템에 제안한 알고리즘을 구현해 본다. 웹 서버에서 웹 로그 분석을 위해 사용한 웹 포렌식 알고리즘과 플로우를 설계하고 코딩을 통한 구현을 한다. 구현 결과 웹 포렌식을 통한 컴퓨터 사이버 범죄에 대한 학문적 기술적 발전에 기여하고자 하는데 본 논문의 목적이 있다.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

• Korean Journal of Culture and Social Issue
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• v.18 no.3
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• pp.329-347
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• 2012

Criminal media such as dramas and movies are growing in popularity. However, the effects of criminal media as well as its psychological mechanism are not clearly examined. Based on social learning theory (Bandura, 1978), past studies showed that arrest and punishment to the criminal in media have a suppressing effect. The present research examined the ironic possibility that media coverage of punishment could increase the audience's criminal intention and proposed the mediating role of counterfactual thinking in the effect. We hypothesized that when punishment was depicted as accidental rather than unavoidable in media coverage, perceived high mutability and counterfactuals focusing on the accidental factors could clarify the ways to commit the crime without being caught and subsequently increase future criminal intention. In this study, 95 college students read a story of plagiarizing either no, accidental, or inevitable punishment, and later asked to report their intention to plagiarize. An ANCOVA with participants' own history of plagiarism as a covariate found that the intention of plagiarism in future was significantly different. The results showed that the intention of plagiarism in the accidental punishment condition was higher than that in the inevitable punishment condition. Further, the intention of plagiarism in the accidental punishment condition was the same level with non-punishment condition. The findings suggest that whether criminals are caught or not is not enough to reduce criminal intentions of audience, but how criminals are caught matters.

• Korean Journal of Forensic Psychology
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• v.12 no.2
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• pp.199-221
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• 2021

The purpose of this study is to examine some factors affecting the decision-making process of white-collar crime. In a between-subject experiment, 102 adult white-collar workers were randomly assigned to a financial pressure condition or tit for tat strategy condition. Participants went through a decision-making process in a modified iterated prisoner's dilemma for a white-collar crime scenario to earn points. The obtained score indicated the risk of committing a crime. The lower the score, the higher was the risk of participating in a crime. The results showed that participants who received only tit for tat strategy information without financial pressure instructions showed the lowest risk of participating in a crime, and those who received only financial pressure without the strategic information had the highest risk of participating in a crime. In addition, those who received the financial pressure instructions were more likely to participate in a crime than those who did not receive financial pressure instructions regardless of the provision of strategic information. The results of this study propose the need for measures to legally relieve financial pressure, the need for education on white-collar crimes for office workers, and the need for a decision-making structure within the enterprise that is not dogmatic but cooperative and mutually verifiable.

• Convergence Security Journal
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• v.18 no.2
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• pp.25-32
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• 2018

As the use of smartphones become more common, the communication via instant messenger becomes natural. However, it is important to secure the relevant information promptly since the chat room between participants can be used as a space for a criminal conspiracy, and crime-related contents can be stored and deleted easily on smartphones. Therefore, this study aims to identify the available data and to use it as proof by comparing and analyzing the instant messengers with high usage rate.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.120-134
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• 2015

Under the hypothesis that the form of road network could affect crime occurrence, this study demonstrates to prove them using Space Syntax with real crime data. We calculated integration, control, connection index by means of Space Syntax and analyzed the relationship between the three indexes and the number of crime occurrence on the each road. Next, in order to generalize the analysis results we adopted Multi-Agent Model and simulated several scenarios on the computer virtual space. The results revealed that integration index has the strongest relationship with crime occurrence both in the case of real study area and virtual space simulations. Though this study has several limitations on the extent of virtual space and realistic computer programming of agents' behavior, the results are meaningful to verify the relationship between the form of read network and crime occurrence. Moreover the simulation platform that this study developed has promising possibilities to find realistic solutions on the effective police deployment or facility layout to improve smart safe city development.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.4
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• pp.93-101
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• 2009

As the industrial society is developing wars, terrors, and vicious crimes is getting increased. These dangerous factors are caused of casualty and subversiveness of social order. Such vicious crimes lead people to feeling of insecurity. That is why naturally people want to build and inspect strengthened security system. CCTV camera system which can be said as the most popular security system is being installed in public places has large number of floating population. This trend is required to develop the intelligent video security technology and propagate it since the importance of security technology is getting high. This thesis will be described regarding the trend of the intelligent surveillance camera and the scenario.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.65-72
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• 2020

With the development of information technology and the growth of the scale of system and network, cyber threats and crimes continue to increase. To cope with these threats, cybersecurity training based on actual attacks and defenses is required. However, cybersecurity training requires expert analysis and attack performance, which is inefficient in terms of cost and time. In this paper, we propose a cyber attack simulator that automatically executes attack techniques. This simulator generates attack scenarios by combining attack techniques modeled to be implemented and executes the attack by sequentially executing the derived scenarios. In order to verify the effectiveness of the proposed attack simulator, we experimented by setting an example attack goal and scenarios in a real environment. The attack simulator successfully performed five attack techniques to gain administrator privileges.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.832-834
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• 2005

유비쿼터스 컴퓨팅의 중요한 핵심 분야인 Situation-Aware 컴퓨팅과 RFID 시스템을 결합한 SA-RFID 시스템을 통해, 제한된 장소에서 범죄나 사고 같은 비정상적인 행동을 예측하기 위한 시스템을 제안하였다. SA-RFID 시스템을 이용한 비정상 행동 예측 시스템은 변형된 SA-RFID Reader 시스템 아키텍쳐와 그에 특화된 SA Middleware를 통해 설계되었고, 비정상 행동 판단 시나리오를 이용하여 명실상부 유비쿼터스 시대에 걸 맞는, 사용자에게 보다 더 안전하고 편안한 생활을 보장해주는 서비스를 제공하게 될 것이다.