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Bibliographic Details
Main Authors: Xie, Jingrong, Li, Yumin
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2510.02378
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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