• 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.

• Convergence Security Journal
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• v.22 no.3
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• pp.79-86
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• 2022

Voice phishing is a cyber crime in which fake financial institutions, the Public Prosecutor's Office, and the National Police Agency are impersonated to find out an individual's Certification number and credit card number or withdraw a deposit. Recently, voice phishing has been carried out in a subtle and secret way. Analyzing the trend of voice phishing that occurred in '18~'21, it was found that there is a seasonality that occurs rapidly at a time when the movement of money is intensifying in the trend of voice phishing, giving ambiguity to time series analysis. In this research, we adjusted seasonality using the X-12 seasonality adjustment methodology for accurate prediction of voice phishing occurrence trends, and predicted the occurrence of voice phishing in 2022 using the ARIMA model.

• 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.

• Korean Security Journal
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• no.62
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• pp.185-203
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• 2020

While overall crime has been on the decline since 2009, voice phishing has rather been on the rise. The government and academia have presented various measures and conducted research to eradicate it, but it is not enough to catch up with evolving voice phishing. In the study, researchers focused on catching criminals and preventing damage from voice phishing, which is difficult to recover from. In particular, a voice phishing prediction method using the Fraud Detection System (FDS), which is being used to detect financial fraud, was studied based on the fact that the victim engaged in financial transaction activities (such as account transfers). As a result, it was conceptually derived to combine big data such as call details, messenger details, abnormal accounts, voice phishing type and 112 report related to voice phishing in machine learning-based Fraud Detection System(FDS). In this study, the research focused mainly on government measures and literature research on the use of big data. However, limitations in data collection and security concerns in FDS have not provided a specific model. However, it is meaningful that the concept of voice phishing responses that converge FDS with the types of data needed for machine learning was presented for the first time in the absence of prior research. Based on this research, it is hoped that 'Voice Phishing Damage Prediction System' will be developed to prevent damage from voice phishing.

• The Journal of the Korea Contents Association
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• v.12 no.7
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• pp.176-182
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• 2012

Voice Phishing finds out personal information illegally using electrification and it is confidence game that withdraw deposit on the basis of this. It appeared by new social problem as damage instances increase rapidly. Target of the damage is invading indiscriminately to good civilian and is crime that commit by foreigners such as a most Chinese, Formosan. Voice Phishing can be crime type of new form in terms of criminal practice is achieved in the foreign countries. Therefore, this study wishes to analyze present occurrence actual conditions and example, and search effective confrontation plan regarding Voice Phishing. Voice Phishing criminal offense is growing as crime is not eradicated in spite of continuous public relations and control, and technique is diversified and specializes preferably. Hereafter, confrontation plan about problem may have to be readied in banking communication investigation to eradicate Voice Phishing. Also, polices control activity may have to be reinforce through quick investigation's practice and development of investigation technique, and relevant government ministry and international mutual assistance cooperation such as the Interpol should be reinforced because is shown international crime personality.

• 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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.5
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• pp.1089-1100
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• 2024

Despite various measures being implemented by the government and related institutions to prevent voice phishing, incidents of such fraud continue to occur. This study analyzed 448 actual conversations between voice phishing scammers and potential victims using text mining techniques. The text analysis reveals that voice phishing scammers frequently use words emphasizing limited time frames such as now, soon, in progress, today, first. This indicates that scammers manipulate the victim's psychology through specific words, preventing them from making rational decisions. The results of this study can aid government and related institutions in formulating effective policies for preventing voice phishing and protecting consumers.

• Journal of the Korea Convergence Society
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• v.6 no.1
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• pp.85-91
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• 2015

Recently government has distributed precautionary measure and response procedures for smishing(SMS phishing), pharming, phishing, memory hacking and intensified Electronic Financial Transaction Act because of the sharp increase of electronic bank frauds. However, the methods of electronic bank frauds also developed and changed accordingly so much it becomes hard to cope with them. In contrast to earlier voice phishing targeted randomizing object, these new methods find out the personal information of targets and analyze them in detail making a big data base. And they are progressed into new kind of electronic bank frauds using those analyzed informations for voice phishing. This study analyze the attack method of voice phishing blended with the Big Data of personal informations and suggests response procedures for electronic bank frauds increasingly developed. Using the method to save meaningless data in a memory, attackers cannot deduct accurate information and try voice phishing properly even though they obtain personal information based on the Big Data. This study analyze newly developed social technologic attacks and suggests response procedures for them.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.157-160
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• 2012

(Voice)Phishing against the old or weak person used the method which is social engineering in the object and financial structure and function. Until recently (voice)Phishing from Chaina caused economic devastation and the economic loss by Phishing grows with the South Korean whole. Korean government and organizations involved have been strengthening protection system and a financial security device. But it is not easy to verify how much effects of security measures are. In this paper we will study the economic loss caused by (voice)Phishing and economic efficiency of security measures and security device reinforcement of the Republic of Korea.

• Journal of Digital Forensics
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• v.13 no.1
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• pp.35-44
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• 2019

The voice-phishing is done by inducing victims to send money, only with voice through the personal information illegally obtained. The amount of damage caused by voice-phishing continues to increase every year, and it became a social problem. Recently, the Financial Supervisory Service (i.e. the FSS) in Republic of Korea has been collecting the voices of voice-phishing scamer from victims. In this paper, we describe an effective forensic speaker analysis method for detecting the voice from the same person compared with the large-scale speech files stored in database(DB), and apply the aforementioned forensic speaker analysis method with the collected voice-phising speech files from victims. At first, an i-vector of each speech file had been extracted from the DB, then, the cosine similarity matrix for the all speech files had been generated through the cosine distance among the extracted the i-vectors of all speech file in DB. In other words, it performed the speaker analysis as grouping a set of candidates with high common similarity among i-vectors of all speech files in DB. As a result of EER(Error Equal Rate) measurement for 6,724 speech files composed of 82 speakers, it was confirmed that the EER of the i-vector-based method is improved than that of the GMM-based method. Finally, as a result of comparing the collected 2,327 voice-phishing speech files collected by the FSS, it was shown that some of the speech files having similar voice features were grouped each other.