• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1045-1046
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• 2023

본 논문은 디지털 소외계층과 사회적 약자를 고려한 보이스피싱 예방 솔루션을 제안한다. 통화 내용을 AWS Transcribe를 활용한 STT와 NLP 알고리즘을 사용해 실시간으로 보이스피싱 위험도를 파악하고 결과를 사용자에게 전달하도록 한다. NLP 알고리즘은 KoBIGBIRD와 DeBERTa 모델 각각을 커스터마이즈하여 보이스피싱 탐지에 적절하게 파인튜닝 했다. 이후, 성능과 인퍼런스를 비교하여 더 좋은 성능을 보인 KoBIGBIRD 모델로 보이스피싱 탐지를 수행한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.95-96
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• 2024

본 논문은 금융 범죄 중 하나인 보이스피싱을 실시간으로 예방하기 위한 탐지 기법을 제안한다. 제안된 모델은 수화기에 출력되는 음성을 녹음하고 네이버 CSR(Cloud Speech Recognition)을 통해 텍스트 파일로 변환한 후 딥러닝 기반의 KoBERT를 바탕으로 다양한 보이스피싱 패턴을 학습하여 실시간 환경에서의 신속하고 정확한 탐지를 위해 실제 통화 데이터를 적절하게 처리하여, 이를 통해 효과적인 보이스피싱 예방에 도움을 줄 것으로 예상된다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1276-1283
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• 2016

The scale of financial damages on voice fishing has not been decreased despite of national and social efforts to reduce the amounts of voice fishing damage. One of these reasons is a sophisticated and vernacular speech style that makes it difficult to recognize the offenders. Furthermore, nowadays, young men have intensively been deceived by not only sophisticated and vernacular speech style which is used the employer of real public offices but also obtained personal information. As a result, this lead directly to the financial damages of younger people who has a stronger judgement than older. For this, we investigated the comparison and analysis between the criminals of voice fishing and the same generation younger people for identifying voice features. The experiment was carried out based on the pitch, bandwidth of pitch, energy, speech speed and voice color for searching the difference of voice characteristics between the criminals of voice fishing and the same generation younger people since 2011. The experimental result shows that there is a significant difference in energy and speech speed between the criminals of voice fishing and the same generation younger people.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.855-857
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• 2019

개인 정보의 확산 및 유출의 문제점으로 인해 보이스 피싱의 피해 건수가 증가하고 있다. 이러한 보이스 피싱의 사회적 문제에 대하여 상황 인지 및 사용자 의도 파악 시스템을 적용하여 해결책으로 제안하고자 한다. 이 시스템은 음성 전화로 이루어지는 순차 정보를 텍스트 데이터에 기반하여 사기범의 문맥적 흐름에서 행위 동사를 추출한다. 추출된 행위 동사의 순차 정보를 통해 보이스 피싱의 상황임을 인지하고, 흐름의 행동 패턴을 분석하여 사기범의 의도를 파악한다. 이러한 상황 인지 및 사용자 의도 파악 시스템은 개인 정보의 문제뿐만 아니라 경제적 피해 규모를 축소시킬 것으로 예상된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.811-814
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• 2021

본 논문에서는 점차 진화되어가는 보이스피싱 수법에 대하여 딥러닝 기반 네트워크인 DNN(Deep Neural Network)를 통한 보이스피싱 여부 판별할 뿐만 아니라, CNN, Bi-LSTM을 활용한 다양한 관점에서의 감성 분석을 통하여 보이스피싱 조직원의 감성 상태를 파악하여 판별된 결과에 신뢰도를 높여주는 모델을 제안하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.214-215
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• 2024

삼성 스마트폰 계정 기반 서비스인 다른 기기에서 전화/문자하기(CMC) 기능이 보이스피싱의 새로운 기술로 동원되고 있다. 기존의 심박스와 같은 불법 중계기보다 발신 번호 변작에 쉽게 활용할 수 있어 CMC 기능을 악용한 보이스피싱 범죄가 증가하고 있으나, 이에 대한 연구가 미비한 현실이다. 본 논문에서는 삼성 기기에서의 CMC 활성화 및 기능 사용 여부에 따른 안드로이드 시스템 로그에서의 차이를 분석하고, 이를 바탕으로 보이스피싱 수사에 활용할 수 있는 포렌식 아티팩트 분석 방법을 제안한다.

• 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.

• 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 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.