Apply Bayes Theorem to Optimize IVR Authentication Process
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866915531031838720 |
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| author | Xie, Jingrong Li, Yumin |
| author_facet | Xie, Jingrong Li, Yumin |
| contents | This paper introduces a Bayesian approach to improve Interactive Voice Response (IVR) authentication processes used by financial institutions. Traditional IVR systems authenticate users through a static sequence of credentials, assuming uniform effectiveness among them. However, fraudsters exploit this predictability, selectively bypassing strong credentials. This study applies Bayes' Theorem and conditional probability modeling to evaluate fraud risk dynamically and adapt credential verification paths. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_02378 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Apply Bayes Theorem to Optimize IVR Authentication Process Xie, Jingrong Li, Yumin Cryptography and Security Statistics Theory Applications This paper introduces a Bayesian approach to improve Interactive Voice Response (IVR) authentication processes used by financial institutions. Traditional IVR systems authenticate users through a static sequence of credentials, assuming uniform effectiveness among them. However, fraudsters exploit this predictability, selectively bypassing strong credentials. This study applies Bayes' Theorem and conditional probability modeling to evaluate fraud risk dynamically and adapt credential verification paths. |
| title | Apply Bayes Theorem to Optimize IVR Authentication Process |
| topic | Cryptography and Security Statistics Theory Applications |
| url | https://arxiv.org/abs/2510.02378 |