• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.431-433
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• 2021

In this paper, abnormal behavior monitoring system using YOLO AI platform was implemented and had superior response characteristics compared to the conventional monitoring system using two-shot detection by using one-shot detection of YOLO system. The YOLO platform was trained using image dataset composed of abnormal behaviors such as assault, theft, and arson. The abnormal behavior monitoring system consists of client and server and can be applicable to smart cities to solve various crime problems if it is commercialized.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.99-106
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• 2023

Now a days, large volumes of data is accumulating in every field due to increase in capacity of storage devices. These large volumes of data can be applied with data mining for finding useful patterns which can be used for business growth, improving services, improving health conditions etc. Data from different sources can be combined before applying data mining. The data thus gathered can be misused for identity theft, fake credit/debit card transactions, etc. To overcome this, data mining techniques which provide privacy are required. There are several privacy preserving data mining techniques available in literature like randomization, perturbation, anonymization etc. This paper proposes an Enhanced Hybrid Privacy Preserving Data Mining(EHPPDM) technique. The proposed technique provides more privacy of data than existing techniques while providing better classification accuracy. The experimental results show that classification accuracies have increased using EHPPDM technique.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.129-130
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• 2020

공중장소에서 충전기에 꽂힌 상태로 무방비로 도난의 위협에 방치되어있는 스마트폰들을 아주 쉽게 발견할 수 있다. 잃어버린 스마트폰은 다시 구매하면 되지만 혹시라도 미처 백업하지 못한 자료나 연락처 등의 소중한 정보의 손실로 인해 피해는 클 것이다. 공중장소에서 충전중인 스마트폰을 절도를 목적으로 무단으로 전원에서 분리할 가능성에 대비하여 경고화면을 보여주는 한편, 만일 무단으로 충전기에서 뽑거나 케이블을 절단하면 경보를 울리는 한편, 현재 위치의 위도와 경도를 SMS기능을 사용해 지정한 전화번호로 해당 정보를 전송하는 기능을 안드로이드에 구현하였다. 이를 통해 도난이 되더라도 스마트폰을 잃어버린 위치와 시간을 특정 할 수 있게 도와 줄 수 있기 때문에, 도난이 의심되는 해당 시설 또는 근처의 CCTV영상을 확보하여 범인을 빨리 특정할 수 있게 함으로써 최대한 빠르게 스마트폰을 되찾을 수 있는 확률을 높여주고, 스마트폰에 대한 절도억제 효과도 줄 수 있다.

• Annual Conference of KIPS
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• 2021.11a
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• pp.1140-1143
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• 2021

예부터 최근까지 세계적으로 해마다 자전거 도난의 문제가 빈번히 발생하고 있고 자전거 자물쇠를 지니고 다녀야 하는 번거로움 또한 발생하고 있다. 현재 자전거 절도가 가장 생활범죄에서 1순위를 차지하고 국가적으로 봐도 많은 도난이 발생하고 있는 나라가 우리나라이지만, 이에 대한 해결책이 미비하며 국가에서의 관심이 턱없이 부족하여, 효율적인 해결방안이 없다. 이러한 문제점을 해결하기 위해 본 논문에서는 현대인에 맞는 스마트한 IOT 자전거 도난 방지 시스템을 제안하고 개발한다. 개발한 시스템은 상황에 맞는 대처 및 시스템 실시간 관리를 통해 사람들이 많이 지니고 다니는 스마트폰에 애플리케이션을 이용하여 긴급상황에 적절하게 대처하여 안전 운행을 가능하게 한다. 또한 현시대에 맞게 휴대성을 위하여 최대한 소형화하고 이에 걸맞은 보안 시스템을 개발함으로써 차후 다양한 분야에 상용화하는 발전 가능성을 기대한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.394-396
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• 2022

After COVID-19, hybrid stores operated as unmanned stores at specific times have spread, and theft crimes against these stores have also increased. In this paper, we propose an intelligent crime prevention system that fully utilizes existing shop devices to identify and respond to crimes occurring during the late night hours of unmanned shops in real time.

• Journal of Information Science Theory and Practice
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• v.11 no.4
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• pp.14-39
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• 2023

Cybercrime is a significant threat to Internet users, involving crimes committed using computers or computer networks. The landscape of cyberspace presents a complex terrain, making the task of tracing the origins of sensitive data a formidable and often elusive endeavor. However, tracing the source of sensitive data in online cyberspace is critically challenging, and detecting cyber-criminals on the other hand remains a time-consuming process, especially in social networks. Cyber-criminals target individuals for financial gain or to cause harm to their assets, resulting in the loss or theft of millions of user data over the past few decades. Forensic professionals play a vital role in conducting successful investigations and acquiring legally acceptable evidence admissible in court proceedings using modern techniques. This study aims to provide an overview of forensic investigation methods for extracting digital evidence from computer systems and mobile devices to combat persistent cybercrime. It also discusses current cybercrime issues and mitigation procedures.

• Annual Conference of KIPS
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• 2023.11a
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• pp.581-582
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• 2023

코로나 19 이후 무인매장에 대한 수요가 꾸준히 증가하며 빠른 시장 규모 성장을 보이고 있다. 그러나 관리자의 부재로 감시가 어렵고 즉각적인 대응이 불가능한 환경으로 인해 도난 문제 또한 꾸준히 발생하고 있다. 본 논문은 YOLO 객체인식 기술을 활용한 무인매장 도난 감지 시스템과 실시간 메일 알림 기능을 제안한다. 이를 통해 무인매장에서 발생하는 도난 범죄를 예방하고, 즉각적인 조치를 가능하게 함으로써 보다 안전하고 효율적으로 무인매장을 관리할 수 있게 한다.

• Asia pacific journal of information systems
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• v.32 no.4
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• pp.857-889
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• 2022

Home theft and burglary are prevalent in Dhaka city. Internet of things (IoT), in contrast, is commonly recognized as among the most advanced home security systems. However, the factors that attract young people to use IoT for household security have yet to be examined. Consequently, the purpose of this article is to validate the attitude-social influence-self-efficacy (ASE) model with personal innovativeness and perceived trust. We collected data from Dhaka citizens aged 15 to 24 using a purposive sample technique and 370 valid responses were chosen for the study. According to the analysis, all of our proposed hypotheses were found significant with a 73.6% variance. Furthermore, the effects of attitude and social influence were shown to be the highest and lowest, respectively, and trust and innovativeness were both nearly strong main predictors of ASE. Significantly, since this is one of the few studies in the technology adoption domain using this model, a solid foundation for IoT adoption for security purposes is established.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.1-10
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• 2024

In the era of big data, the growth of e-commerce transactions brings forth both opportunities and risks, including the threat of data theft and fraud. To address these challenges, an automated real-time fraud detection system leveraging machine learning was developed. Four algorithms (Decision Tree, Naïve Bayes, XGBoost, and Neural Network) underwent comparison using a dataset from a clothing website that encompassed both legitimate and fraudulent transactions. The dataset exhibited an imbalance, with 9.3% representing fraud and 90.07% legitimate transactions. Performance evaluation metrics, including Recall, Precision, F1 Score, and AUC ROC, were employed to assess the effectiveness of each algorithm. XGBoost emerged as the top-performing model, achieving an impressive accuracy score of 95.85%. The proposed system proves to be a robust defense mechanism against fraudulent activities in e-commerce, thereby enhancing security and instilling trust in online transactions.

• Journal of the Korean Regional Science Association
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• v.31 no.4
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• pp.3-24
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• 2015

Crimes must be reduced not only because of the financial, physical, and emotional damages they bring to the victims but also because crimes increase social costs by elevating distrust in society and instilling fear. With the increasing number of crimes in Korea, finding other factors that affect the occurrence of crimes is needed beyond the current viewpoint for crime analysis. Social support factors can be candidates for studies on the social support effect on crime occurrence in their initial stage. In this study, we identified the effect of social support factors on crime occurrence or deterrence, none of which has been considered important until now, given the emergence of spatial econometrics. The resulting Moran's I values revealed the existence of a spatial autocorrelation in all three crimes: heinous crimes, theft, and violence. As shown in the analysis using spatial econometrics and ordinary least squares, social support from families is significant in reducing all crimes especially violence. Social support from the local government is significant in preventing only theft. The spatial econometrics model is only valid in heinous crimes. These different effects of social support factors and spatial factors on crime occurrences are caused by the different characteristics of crimes. Hence, policymakers should consider the social support effect when they establish policies related to social housing or welfare.