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<p>The increasing sophistication of cyber attacks has rendered traditional static password-based authentication mechanisms inadequate for secure identity verification in modern information systems. Attack techniques such as social engineering, credential theft, and phishing continue to bypass conventional security controls, underscoring the need for adaptive, continuous identity verification mechanisms within Zero Trust architectures. A multi-layer identity authentication architecture is developed by integrating Multi-Factor Authentication (MFA) with the Analysis of Competing Hypotheses (ACH) to enable dynamic and robust access control. The architecture adopts a three-layer verification framework that progresses from basic identity validation to advanced behavioral analysis. It consists of an Identity Authentication Engine, an ACH Engine, and a Policy Engine, which collectively perform multidimensional behavioral assessment across five factors: login time patterns, device characteristics, geolocation, user operational behavior, and network environment attributes. By replacing static, one-time authentication with continuous identity assessment, the proposed framework enforces strict verification at initial access and maintains real-time monitoring throughout the entire user session. This approach enables the detection of anomalous behavior and potential threats even when valid credentials are compromised. The architecture is evaluated using simulated financial transaction scenarios. Experimental results show that the system achieves 94.3% accuracy in identifying legitimate access and 96.1% accuracy in detecting automated attacks. Compared with traditional two-factor authentication methods, the framework reduces the false-positive rate by 57% and the false-negative rate by 47%. These results demonstrate that combining ACH, MFA, behavioral analysis, and continuous monitoring significantly enhances authentication reliability in Zero Trust environments and provides a practical, deployable solution for secure identity verification.</p>

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A Hypothesis-Driven Multi-layer Zero Trust Authentication Framework

  • 期刊论文

  • 发表日期：

    2026年6月27日

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  • Shih-Hao Chang,
  • Kai-li Huang,
  • Wen-Bin Hsieh,
  • Shiang-Jiun Chen

摘要

The increasing sophistication of cyber attacks has rendered traditional static password-based authentication mechanisms inadequate for secure identity verification in modern information systems. Attack techniques such as social engineering, credential theft, and phishing continue to bypass conventional security controls, underscoring the need for adaptive, continuous identity verification mechanisms within Zero Trust architectures. A multi-layer identity authentication architecture is developed by integrating Multi-Factor Authentication (MFA) with the Analysis of Competing Hypotheses (ACH) to enable dynamic and robust access control. The architecture adopts a three-layer verification framework that progresses from basic identity validation to advanced behavioral analysis. It consists of an Identity Authentication Engine, an ACH Engine, and a Policy Engine, which collectively perform multidimensional behavioral assessment across five factors: login time patterns, device characteristics, geolocation, user operational behavior, and network environment attributes. By replacing static, one-time authentication with continuous identity assessment, the proposed framework enforces strict verification at initial access and maintains real-time monitoring throughout the entire user session. This approach enables the detection of anomalous behavior and potential threats even when valid credentials are compromised. The architecture is evaluated using simulated financial transaction scenarios. Experimental results show that the system achieves 94.3% accuracy in identifying legitimate access and 96.1% accuracy in detecting automated attacks. Compared with traditional two-factor authentication methods, the framework reduces the false-positive rate by 57% and the false-negative rate by 47%. These results demonstrate that combining ACH, MFA, behavioral analysis, and continuous monitoring significantly enhances authentication reliability in Zero Trust environments and provides a practical, deployable solution for secure identity verification.