• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2341-2346
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• 2012

Voice phishing against the old or weak persons have used the methods which are 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 Koreans in the whole. Korean government and public organizations involved have been strengthening protection system and a financial security devices. But it is not easy to verify how much effects of security measures are. In this paper I will study the economic loss caused by voice phishing and potential economic effects of security measures and security device reinforcements of the Republic of Korea. Direct costs are reported about 100 million dollars and potential economic effects of voice phinshing secure measures may be around 320 million dollars.

• Convergence Security Journal
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• v.24 no.2
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• pp.151-160
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• 2024

In recent years with high interest rates and inflations, which worsen people's lives, voice phishing crimes also increase along with damage. Voice phishing that becomes more evolved by technology developments causes serious financial and mental damage to victims. This work aims to study time series models for its accurate prediction. ARIMA, SARIMA and SARIMAX models are compared. As exogenous variables, the amount of damages and the numbers of arrests and criminals are adopted. Forecasting performances are evaluated. Prediction intervals are constructed along with empirical coverages, which justify the superiority of the model. Finally, the numbers of voice phishing up to December 2024 are predicted, through which we expect the establishment of future prevention strategies for voice phishing.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.791-805
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• 2022

In recent years, the number of scams related to voice phishing has been on the decline, but the number of messenger phishing attacks, a new type of crime, is increasing. In this study, by analyzing SNS posts containing messenger phishing cases, criminal trends of the main methods, imposture of trusted relative and fake payment were identified. Through the analysis, main words and patterns composing the message and the similarity and continuity of the phone numbers used were derived as criminal attributes, and criminal organizations were grouped. As the results of the analysis, we propose a cooperative system to prevent damage from messenger phishing by disseminating the criminal information collected by investigative agencies to private operators, and a plan to respond to messenger phishing predicted through grouping of criminal organizations.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.10
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• pp.437-446
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• 2022

Text classification task from Natural Language Processing (NLP) combined with state-of-the-art (SOTA) Machine Learning (ML) and Deep Learning (DL) algorithms as the core engine is widely used to detect and classify voice phishing call transcripts. While numerous studies on the classification of voice phishing call transcripts are being conducted and demonstrated good performances, with the increase of non-face-to-face financial transactions, there is still the need for improvement using the latest NLP technologies. This paper conducts a benchmarking of Korean voice phishing detection performances of the pre-trained Korean language model KoBERT, against multiple other SOTA algorithms based on the classification of related transcripts from the labeled Korean voice phishing dataset called KorCCVi. The results of the experiments reveal that the classification accuracy on a test set of the KoBERT model outperforms the performances of all other models with an accuracy score of 99.60%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.138-142
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• 2009

We propose an effective voice-phishing detection algorithm based on discriminative weight training. The detection of voice phishing is performed based on a Gaussian mixture model (GMM) incorporaiting minimum classification error (MCE) technique. Actually, the MCE technique is based on log-likelihood from the decoding parameter of the SMV(Selectable Mode Vocoder) directly extracted from the decoding process in the mobile phone. According to the experimental result, the proposed approach is found to be effective for the voice phishing detection.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1267-1277
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• 2021

The phone number used for advertising messages and voices used as bait in the voice phishing crime access stage is being used to send out a large amount of illegal loan spam, so we want to quickly block it. In this paper, our system is designed to block the usage of the phone number by rapidly restricting the use of the voice spam phone number that conducts illegal loan spam and voice phishing, and at the same time sends continuous calls to the phone number to prevent smooth phone call connection. The proposed system is a representative collaboration model between an illegal spam reporting agency and an investigation agency. As a result of developing the system and applying it in practice, the number of reports of illegal loaned voice spam and text spam decreased by 1/3, respectively. We can prove the effectiveness of this system by confirming that.

• Convergence Security Journal
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• v.14 no.5
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• pp.65-74
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• 2014

Phishing scans through wired telephones have been evolving into smissing and pharming. While we use wire or wireless telephones, text messages, e-mails, and online-banking conveniently, the ways of hacking and phishing attacks are getting developed and various. This paper investigates the various aspects of attacks depending on the kinds of phishing and suggests general prevention measures. In addition, the user-oriented practical preventive measures and government-driven long term measures are proposed in this paper. Technological developments, short or long term preventive measures proposed by the government, and continuous public relations could be solutions since in a short time, it could be difficult to eradicate phishing scams evolving continuously. Besides, the internet media as well as SNS are great helps in promoting the preventives against phishing and smissing. Finally this paper asserts that the newly developed service technology should be made carefully without security problems.

• Journal of the Korea Convergence Society
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• v.2 no.4
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• pp.9-14
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• 2011

Phishing is an attack to theft an user's identity by masquerading the user or the device. The number of phishing victims are sharply increased due to wide spread use of smart phones and messenger programs. Smart phones can operate various wi-fi based apps besides typical voice call and SMS functions. Generally, the messenger program such as Kakao Talk or Nate On is consisted of client and server functions. Thus, the authentication between the client and the server is essential to communicate securely. In this paper, we propose the messenger authentication protocol safe against smart phone phishing. To protect communications among clients, the proposed method provides message encryption and authentication functions.

• Annual Conference of KIPS
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• 2019.10a
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• pp.156-159
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• 2019

The damage from voice phishing reaches one trillion won in the past 5 years following report of Business Korea on August 28, 2018. Voice phishing and mobile phone scams are recognized as a top concern not only in Korea but also in over the world in recent years. In this paper, we propose an efficient system to identify the caller and alert or prevent of dangerous to users. Our system includes a mobile application and web server using client and server architecture. The main purpose of this system is to automatically display the information of unidentified callers when a user receives a call or message. A mobile application installs on a mobile phone to automatically get the caller phone number and send it to the server through web services to verify. The web server applies a machine learning to a global phone book with Blacklist and Whitelist to verify the phone number getting from the mobile application and returns the result.

• Annual Conference of KIPS
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• 2009.11a
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• pp.647-648
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• 2009

'보이스피싱(Voice Phishing)'은 전화를 통해 자신을 신뢰할 수 있는 대상으로 위장하여 개인 정보를 훔치는 행위이다. 최근 들어 보이스피싱 피해 사례가 급증하고 있으며 아직 딱히 대안이 없는 상태이다. 또한, IP 환경에서의 전화통화는 보이스피싱을 더욱 용이하게 하고 있다. 본 논문에서는 VoIP 환경에서 공개키 암호화 기법을 이용하여 발신자의 신원을 정확히 밝히는 인증을 통해 사용자가 악성 발신자에게 정보를 제공하거나 금전적 피해를 피할 수 있는 방법론을 제시한다. 이를 통해 사용자는 발신자의 정확한 신원 정보를 제공 받아 보이스피싱 당할 가능성을 줄일 수 있다.