• 한국컴퓨터정보학회논문지
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• 제13권2호
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• pp.143-151
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• 2008

인터넷 이용자의 74%가 UCC를 이용하고 있고, You Tube를 이용한 총기범죄가 발생하였다. 인터넷 범죄는 온라인에서 비대면성, 익명성, 은닉성으로 발생되고 있다. 본 논문에서는, 인터넷 UCC속에 나타난 인터넷 범죄의 양태를 분석하고 추적하는 네트워크 포렌식 방법과 기법을 연구한다. 인터넷 UCC의 범죄와 관련된 경찰과 검찰의 UCC 검색 방법 연구와 저장방법을 이용한 UCC의 증거 자료 수집 및 네트워크 포렌식을 통한 ID, IP 역추적과 위치 추적을 연구한다. 증거자료는 암호화하여 저장하며 접근제어와 사용자 인증을 통한 전송 및 저장 후에 무결성 검증을 통해 법정의 증거자료로 채택되도록 연구한다. 본 연구를 통해 인터넷 범죄 모의와 발생 등을 사전에 차단할 수 있도록 추진하고, 수사기관의 인터넷 범죄에 대한 포렌식 연구 발전에 기여하게 될 것이다.

• Communications for Statistical Applications and Methods
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• 제17권3호
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• pp.413-421
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• 2010

본 연구에서는 5대 범죄중 사람의 생명과 신체에 심각한 위해를 가하는 강력범죄인 살인과 강도 범죄의 이변량 가산자료에 대해 이변량조건부자기회귀모형을 사용하여 공간상관성을 반영한 강력범죄모형을 제안하였다. 범죄자료와 같은 가산자료에 대한 과대산포 검정을 위해 우도비 검정 실시하였으며, 그 결과 과대산포가 유의하지 않음에 따라 공간포아송모형을 이용하였다. 실증예제로 2007년 서울시에서 제공하는 25개 자치구별 강력범죄자료를 지리정보시스템을 이용하여 강력범죄 발생실태를 시각화하였으며 강력범죄에 영향을 주는 다양한 요인들에 대하여 분석을 실시하였다.

• 디지털산업정보학회논문지
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• 제6권3호
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• pp.79-89
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• 2010

Cellular and Smart phone through the business and real life is associated with an increasing number of information processing, Breaches associated with mobile terminal Tile has occurred and cause Crime and damage. In this paper, Cellular and Smart phone for mobile forensics SYN scheme and JTAG scheme to target Cellular and Smart phone for the extraction of forensic data will be studied. SYN, JTAG approach to forensic analysis indicate with the process, Every Smart phone's OS specific performance and data extraction were compared. In the laboratory, Cell and smart phone with the SYN scheme and JTAG scheme to extract forensic data Improvement compared to the extraction is presented.

• 한국컴퓨터정보학회논문지
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• 제22권11호
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• pp.97-104
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• 2017

Location prediction has been successfully utilized to provide high quality of location-based services to customers in many applications. In its usual form, the conventional type of location prediction is to predict future locations based on user's past movement history. However, as location prediction needs are expanded into much complicated cases, it becomes necessary quite frequently to make inference on the locations that target user visited in the past. Typical cases include the identification of locations that infectious disease carriers may have visited before, and crime suspects may have dropped by on a certain day at a specific time-band. Therefore, primary goal of this study is to predict locations that users visited in the past. Information used for this purpose include user's demographic information and movement histories. Data mining classifiers such as Bayesian network, neural network, support vector machine, decision tree were adopted to analyze 6868 contextual dataset and compare classifiers' performance. Results show that general Bayesian network is the most robust classifier.

• 한국멀티미디어학회논문지
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• 제25권8호
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• pp.1049-1058
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• 2022

HAR(Human Action Recognition) such as anomaly and object detection has become a trend in research field(s) that focus on utilizing Artificial Intelligence (AI) methods to analyze patterns of human action in crime-ridden area(s), media services, and industrial facilities. Especially, in real-time system(s) using video streaming data, HAR has become a more important AI-based research field in application development and many different research fields using HAR have currently been developed and improved. In this paper, we propose and analyze a deep-learning-based HAR that provides more efficient scheme(s) using an intelligent AI models, such system can be applied to media services using RGB video streaming data usage without feature extraction pre-processing. For the method, we adopt Slowfast based on the Deep Neural Network(DNN) model under an open dataset(HMDB-51 or UCF101) for improvement in prediction accuracy.

• The Journal of Asian Finance, Economics and Business
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• 제7권7호
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• pp.475-487
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• 2020

The paper aims to facilitate a discussion around how big data technologies and data from citizens can be used to help public administration, society, and policy-making to improve community's lives. This paper discusses opportunities and challenges of big data strategies for government, society, and policy-making. It employs the presentation of numerous practical examples from different parts of the world, where public-service delivery has seen transformation and where initiatives have been taken forward that have revolutionized the way governments at different levels engage with the citizens, and how governments and civil society have adopted evidence-driven policy-making through innovative and efficient use of big data analytics. The examples include the governments of the United States, China, the United Kingdom, and India, and different levels of government agencies in the public services of fraud detection, financial market analysis, healthcare and public health, government oversight, education, crime fighting, environmental protection, energy exploration, agriculture, weather forecasting, and ecosystem management. The examples also include smart cities in Korea, China, Japan, India, Canada, Singapore, the United Kingdom, and the European Union. This paper makes some recommendations about how big data strategies transform the government and public services to become more citizen-centric, responsive, accountable and transparent.

• ETRI Journal
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• 제44권2호
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• pp.300-312
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• 2022

Recently, public safety services have attracted significant attention for their ability to protect people from crimes. Rapid detection of dangerous situations (that is, abnormal situations where someone may be harmed or killed) is required in public safety services to reduce the time required to respond to such situations. This study proposes a novel danger detection technology based on multimodal data, which includes data from multiple sensors (for example, accelerometer, gyroscope, heart rate, air pressure, and global positioning system sensors), and multilog data, which includes contextual logs of humans and places (for example, contextual logs of human activities and crime-ridden districts) over time. To recognize human activity (for example, walk, sit, and punch), the proposed technology uses multimodal data analysis with an attitude heading reference system and long short-term memory. The proposed technology also includes multilog data analysis for detecting whether recognized activities of humans are dangerous. The proposed danger detection technology will benefit public safety services by improving danger detection capabilities.

• 대한인간공학회지
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• 제30권2호
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• pp.319-330
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• 2011

In computer forensics investigation, the investigators collect, protect, analyze and interpret massive amount of data which were used in cyber crime. However, due to its huge amount of information, it takes a great deal of time and errors often result even when they use forensics investigation tool in the process. The information visualization techniques will greatly help to improve the information processing ability of human when they deal with the overwhelming amount of data and have to find out significant information in it. The importance of Intrusion Detection System(IDS) among network forensics is being emphasized in computer forensics. In this study, we apply the information visualization techniques which are proposed to be a great help to IDS and carry out the usability test to find out the most effective information visualization techniques for IDS.

• 한국주거학회논문집
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• 제8권2호
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• pp.49-59
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• 1997

The purpose of this study is to analyze Phenomenon of the residential movement and important factors in the city of Seoul. First, The patterns of residential location during 1975-1994 in terms of macro aspects are to be investigated. Second, Residential patterns among households based on the literature survey data in terms of micro aspects are to be indentified. Methodology applied to the study is regression analysis using 1975-1994statistical data and content analysis based on the literature survey. The results of this study are as follows : 1) The factors of residential movement in the city of Seoul are explained by the changes of the economic structure, residential environment, individual characteristics, and housing policy. That is. the development of transportation systems, the number of homeownership scheme holders, crime rates, increase of residential areas effect on the decrease of the population in the city center of Seoul 2) According to the income groups and resident characteristics, Residential location patterns are different in residential location choice and the scope of spatial migration.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1237-1250
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• 2006

In this paper we develop the web-based unified randomized response system for obtaining more reliable response to the sensitive characteristic such as a crime of violence at home, and a bribing and so on. This survey system embody to apply with from the classical to recently research, for example from the Warner's model to the 2-stage model. In addition, our survey system is able to link between the typical and the randomized response system. Finally, our survey system looks into a variation according to various sensitive questions as well as it can be used for a single question.