• Journal of Digital Convergence
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• v.16 no.10
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• pp.333-342
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• 2018

The objective of this study was to investigate the problem behavior and its convergent factors in out-of-school adolescents, with a focus on gender differences. This study was a secondary data analysis study using out-of-school adolescents research data at Busan women and family development institute. The study was conducted in a total of 499 out-of-school adolescents (337 males, 162 females). The type of the 8 problem behaviors (run away from home, drop out, prostitution, violence, internet game addiction, theft, drug addiction, and smoking) were identified. The collected data were analyzed with multiple logistic regression. Among the problem behaviors of the participants, internet game addiction and theft were more significantly high in male out-of-school adolescents than female out-of-school adolescents. In internet game addiction, male out-of-school adolescents were 1.90 times higher than female out-of-school adolescents (p=.008, 95% CI=1.18-3.06). In theft, male out-of-school adolescents were 1.92 times higher than female out-of-school adolescents (p=.006, 95% CI=1.21-3.03). When the social measures were provided for those adolescents, a distinguished approach is required depending on the problem behavior and gender.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.3
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• pp.627-637
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• 2015

As game item trading becomes more popular with the rapid growth of online game market, the market for trading game items by cash has increased up to KRW 1.6 trillion. Thanks to this active market, it has been easy to turn these items and game money into real money. As a result, some malicious users have often attempted to steal other players' rare and valuable game items by using their account. Therefore, this study proposes a detection model through analysis on these account thieves' behavior in the Massive Multiuser Online Role Playing Game(MMORPG). In case of online game identity theft, the thieves engage in economic activities only with a goal of stealing game items and game money. In this pattern are found particular sequences such as item production, item sales and acquisition of game money. Based on this pattern, this study proposes a detection model. This detection model-based classification revealed 86 percent of accuracy. In addition, trading patterns when online game identity was stolen were analyzed in this study.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.119-125
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• 2021

As the electricity grid systems has been intelligent with the development of ICT technology, power consumption information of users connected to the grid is available to acquired and analyzed for the power utilities. In this paper, the energy theft problem is solved by feature selection methods, which is emerging as the main cause of economic loss in smart grid. The data preprocessing steps of the proposed system consists of five steps. In the feature selection step, features are selected using analysis of variance and mutual information (MI) based method, which are filtering-based feature selection methods. According to the simulation results, the performance of support vector machine classifier is higher than the case of using all the input features of the input data for the case of the MI based feature selection method.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.401-406
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• 2018

According to the National Security Service of the National Police Agency, intrusion into empty houses increased form 2013 to 2016. Consequentially this statistics seemed that house intrusion, burglary is increasing. Also according to the statistics of Public Prosecutors'Office, a total 203,573 theft crimes occurered in 2016, of which 18.9% were theft after intruding. By reson of this is most frequent case of intrusion and theft, we have been studing the RodSecurityRobot model to enhance security in many factories to manage. In order to care for security to the high place, we have propsed a road guard robot model which controls the ground in cooperation with the robot that manages the ground by using the drones. The robot and the drone move together to autonomy to avoid objects. And they check time interval. they also goes to the charger to charge when there is no battery.

• Convergence Security Journal
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• v.22 no.4
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• pp.99-107
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• 2022

The use of smart home appliances and Internet of Things (IoT) devices is growing, enabling new interactions and automation in the home. This technology relies heavily on mobile services which leaves it vulnerable to the increasing threat of hacking, identity theft, information leakage, serious infringement of personal privacy, abnormal access, and erroneous operation. Confirming or proving such security breaches have occurred is also currently insufficient. Furthermore, due to the restricted nature of IoT devices, such as their specifications and operating environments, it is difficult to provide the same level of internet security as personal computers. Therefore, to increase the security on smart home IoT devices, attention is needed on (1) preventing hacking and user authority theft; (2) disabling abnormal manipulation; and (3) strengthening audit records for device operation. In response to this, we present a plan to build a cloud security authentication platform which features security authentication management functionality between mobile terminals and IoT devices.

• Korean Security Journal
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• no.34
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• pp.313-336
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• 2013

The purpose of this study is to derive an optimal regression model for occurrences of major crimes on a security company's stock price through identifying precedence of the occurrences of major crimes on the security company's stock price, relationship between the occurrences of major crimes and the security company's stock price. Followings are the results of this study. First, the occurrences of murder crime, robbery crime, rape crime, theft crime move along the security company's monthly stock price simultaneously, and the occurrence of violence crime precedes 6 months to the security company's monthly stock price depending on the results of cross-correlation analysis of precedence of occurrences of major crimes, such as murder crime, robbery crime, rape crime, theft crime, violence crime on the security company's monthly stock price. Second, the explanation of the occurrences of robbery crime, rape crime, theft crime on the security company's monthly stock price is 61.7%($R^2$ = .617) excluding murder crime, violence crime depending on the results of multiple regression analysis(stepwise method) by putting the occurrences of major crimes, such as murder crime, robbery crime, rape crime, theft crime, violence crime into the security company's monthly stock price.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.3
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• pp.15-25
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• 2017

As the value and importance of softwares are growing up, software theft and piracy become a much larger problem. To tackle this problem, it is highly required to provide an accurate method for detecting software theft and piracy. Especially, while software theft is relatively easy in the case of Android applications (apps), screening illegal apps has not been properly performed in Android markets. In this paper, we propose a method to effectively measure the similarity between Android apps for detecting software theft at the executable file level. Our proposed method extracts method reference frequency and manifest information through static analysis of executable Android apps as the main features for similarity measurement. Each app is represented as an n-dimensional vectors with the features, and then cosine similarity is utilized as the similarity measure. We demonstrate the effectiveness of our proposed method by evaluating its accuracy in comparison with typical source code-based similarity measurement methods. As a result of the experiments for the Android apps whose source file and executable file are available side by side, we found that our similarity degree measured at the executable file level is almost equivalent to the existing well-known similarity degree measured at the source file level.

• Journal of Convergence Society for SMB
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• v.4 no.1
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• pp.41-45
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• 2014

Only if the secret key stored in the engine ECU matches car key stored in the car, immobilizer system is a car anti-theft system that automobile engine takes. To take an action as soon in case of losing car key or being stolen, the ASPI protocol is proposed for assigning a new password after finishing user authentication by the smart phone etc. The shortcoming point of that directly bring the car to a service center in case of losing key can be complemented by the proposed protocol. In case of the car and key both are theft together, the car can be stopped soon.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4508-4528
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• 2016

Widespread use of wireless networks has drawn attention to ascertain confidential communication and proper authentication of an entity before granting access to services over insecure channels. Recently, Truong et al. proposed a modified dynamic ID-based authentication scheme which they claimed to resist smart-card-theft attack. Nevertheless, we find that their scheme is prone to smart-card-theft attack contrary to the author's claim. Besides, anyone can impersonate the user as well as service provider server and can breach the confidentiality of communication by merely eavesdropping the login request and server's reply message from the network. We also notice that the scheme does not impart user anonymity and forward secrecy. Therefore, we present another authentication scheme keeping apart the threats encountered in the design of Truong et al.'s scheme. We also prove the security of the proposed scheme with the help of widespread BAN (Burrows, Abadi and Needham) Logic.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.7
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• pp.95-100
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• 2012

Currently, crimes are becoming increasingly dense, the technique is also very tricky. Pickpocket, the theft of crime, is occurred at the most crowded or congested places. However, nowadays occurs more commonly at the rare and secluded place in the human. In this paper, we investigate the techniques and types of pickpockets. And realistically to submit classified video, to standing, sitting, and lying to the classification. Target for pickpockets, we classify it to submit a video forensic evidence. This paper will be needed in order to prevent and cope with pickpockets crimes.