• ETRI Journal
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• v.31 no.1
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• pp.92-94
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• 2009

We propose a system for mobile-phone fraud detection based on a bidirectional artificial neural network (bi-ANN). The key advantage of such a system is the ability to detect fraud not only by offline processing of call detail records (CDR), but also in real time. The core of the system is a bi-ANN that predicts the behavior of individual mobile-phone users. We determined that the bi-ANN is capable of predicting complex time series (Call_Duration parameter) that are stored in the CDR.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3723-3737
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• 2022

Google Play is one of the largest Android phone app markets and it contains both free and paid apps. It provides a variety of categories for every target user who has different needs and purposes. The customer's rate every product based on their experience of apps and based on the average rating the position of an app in these arch varies. Fraudulent behaviors emerge in those apps which incorporate search rank maltreatment and malware proliferation. To distinguish the fraudulent behavior, a novel framework is structured that finds and uses follows left behind by fraudsters, to identify both malware and applications exposed to the search rank fraud method. This strategy correlates survey exercises and remarkably joins identified review relations with semantic and behavioral signals produced from Google Play application information, to distinguish dubious applications. The proposed model accomplishes 90% precision in grouping gathered informational indexes of malware, fakes, and authentic apps. It finds many fraudulent applications that right now avoid Google Bouncers recognition technology. It also helped the discovery of fake reviews using the reviewer relationship amount of reviews which are forced as positive reviews for each reviewed Google play the android app.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.201-204
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• 2013

From 2009 to the present, smart phone users has been steadily increasing. And through the use of smart phone applications, smart phone user can perform easily what they want to do whenever and wherever. However, new types of financial fraud such as phishing, pharming and smishing are appeared exploiting these advantages. Accordingly in this paper, I propose to prevent social issues like phishing, pharming and smishing for the technical way using mobile hypervisor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.394-397
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• 2014

Most of Koreans have smartphone. By using smartphone, they have done internet-banking, e-commerce and private scheduling. However, convenience of smart phone has been made side effect such as tool of fraud and crime. Especially, Smishing on smartphone has been increased rapidly since 2013. Smishing have utilized social-engineering technique with social issue such as Korean near-sea cruse ship, 'Sewol-Ho', Sinking and traditional thanks-giving holiday, 'Chu-Seok', etc. This paper proposed the oncoming trend of smishing on smartphone after 2014. This paper also analyzed the process and technique of smishing on internal financial fraud. It also covered smartphone forensic for using legal evidence. By discovering the connectivity of smishing and financial fraud, this paper could be reference for social security on smartphone.

• Journal of Information Technology Services
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• v.15 no.2
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• pp.35-49
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• 2016

With the gradual development of IT technology, voice phishing victims are increasing in number. In the past when only voice phone calls were made, personal information or financial information were stolen mainly by a direct phone call, but recently, as smart phones are widely in use, it is evolving into a way such as smishing that leads an access to a site with malicious codes spreading out. Since it is easy to run away after committing a crime, and trace are rarely left in case of voice phishing, it is difficult to find out criminal. In addition, it is most likely that a victim be would be exposed to further damage from another voice phishing. Its technique is growing in kinds and turning more intelligent day by day; Therefore, its victims are increasing in number. Previous researches mainly focused the area of legal studies while the factors exposed to voice phishing have not been made. Therefore, this study has analyzed the motifs in which voice phishing is done to draw out its outcomes as follows. First, a victim comes to trust the criminal by the factors of favorability, rare message, and mutuality. Second, the more sophisticated the technique of a criminal, the more likely a victim is exposed to voice phishing.

• Journal of Korean Medical classics
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• v.30 no.3
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• pp.133-141
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• 2017

Objectives : As of 2013, South Korea ranked number one in the world in smartphone penetration rate with 67.6%. Unfortunately, with the rise of smart phone use, side effects such as fraud, loss of personal information, identity theft, formation and widening of a mobile information gap, and last, but not least, smart phone addiction, also increased. Methods : Seventh (7th)graders from a girls' junior high school in Seoul, the capital of South Korea, we reevaluated the Smart phone Addiction Proneness Scale (S-scale). Among the 9 students classified as high risk users, 5 were randomly selected for a study group, and the remaining 4 students, meanwhile, were designated as a control group. The study group received Korean medicine music therapy (KMMT) in a total of 8 sessions, each session lasting 50 minutes. Both pre- and post-interventions, the two groups completed the S-scale, Harris and Harris' concentration grid exercise, STAI, and STAXI-K. We analyzed the data by t-test and paired t-test using IBM SPSS Statistics. Results : KMMT had a significant influence on proneness to smart phone addiction (t=3.130, p=.035). KMMT had positive effects on concentration improvement (t=-2.935, p=.043), trait-anxiety symptoms improvement (t=2,992, p=.040), and anger-expression control (t=4.416, p=.012). Conclusions : KMMT had positive, improving effects on trait anxiety and anger expression, which in turn enhanced the improvement of concentration as well as the decrease of smart phone-addiction proneness.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.173-182
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• 2022

In this paper, we propose a machine learning model that can prevent fraudulent transactions in advance and interpret them using the XAI approach. For the experiment, we collected a real data set of 12,258 mobile phone sales posts from Joonggonara, a major domestic online C2C resale trading platform. Characteristics of the text corresponding to the post body were extracted using Doc2vec, dimensionality was reduced through PCA, and various derived variables were created based on previous research. To mitigate the data imbalance problem in the preprocessing stage, a complex sampling method that combines oversampling and undersampling was applied. Then, various machine learning models were built to detect fraudulent postings. As a result of the analysis, LightGBM showed the best performance compared to other machine learning models. And as a result of SHAP, if the price is unreasonably low compared to the market price and if there is no indication of the transaction area, there was a high probability that it was a fraudulent post. Also, high price, no safe transaction, the more the courier transaction, and the higher the ratio of 0 in the price also led to fraud.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.2
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• pp.11-22
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• 2015

The almost of Web page has been gathered the personal information(Korean resident registration number, name, cell-phone number, home telephone number, E-mail address, home address, etc.) using the membership and log-in. The all most user of Web page are concerned for gathering of the personal information. I-pin is the alternative means of resident registration number and has been used during the last ten-year period in the internet. The accident of I-pin mass illegal issue was happened by hacker at February, 2015. In this paper, we analysis the problems of I-pin system about I-pin mass illegal issue accident and propose a improvement method of it. First, I-pin issue must be processed by the off-line of face certification in spite of user's inconvenience. Second, I-pin use must be made up through second certification of password or OTP. The third, the notification of I-pin use must be sent to the user by the text messaging service of cell-phone or the E-mail. The forth, I-pin must be used an alternative means of Korean resident registration number in Internet. The methods can reduce the problems of I-pin system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.704-719
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• 2024

Botnet pandemics are becoming more prevalent with the growing use of mobile phone technologies. Mobile phone technologies provide a wide range of applications, including entertainment, commerce, education, and finance. In addition, botnet refers to the collection of compromised devices managed by a botmaster and engaging with each other via a command server to initiate an attack including phishing email, ad-click fraud, blockchain, and much more. As the number of botnet attacks rises, detecting harmful activities is becoming more challenging in handheld devices. Therefore, it is crucial to evaluate mobile botnet assaults to find the security vulnerabilities that occur through coordinated command servers causing major financial and ethical harm. For this purpose, we propose a hybrid analysis approach that integrates permissions and API and experiments on the machine-learning classifiers to detect mobile botnet applications. In this paper, the experiment employed benign, botnet, and malware applications for validation of the performance and accuracy of classifiers. The results conclude that a classifier model based on a simple decision tree obtained 99% accuracy with a low 0.003 false-positive rate than other machine learning classifiers for botnet applications detection. As an outcome of this paper, a hybrid approach enhances the accuracy of mobile botnet detection as compared to static and dynamic features when both are taken separately.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.193-198
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• 2018

In Korea, the penetration rate of Internet, telephone and smart devices is reaching the highest level in the world. Cyber financial crimes that exploit such infrastructures continue to evolve. Since the first Voice Phishing crime in May 2006, ten years later, there has been a constant occurrence of Voice Phishing crime. Voice Phishing is a crime in which a victim is phoned for false information to figure out the victim's account number and password. This method of Voice Phishing evolves day by day, and it is difficult to investigate. Most of Voice Phishing is a form of international organized crime that is based in Southeast Asia such as China, and it is not easy to eradicate by international cooperation investigation. The purpose of this study is to investigate the actual situation and case analysis of Voice Phishing crime, and to propose the countermeasures against police Voice Phishing counterplan.