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SecureBank: A Financially-Aware Zero Trust Architecture for High-Assurance Banking Systems
arXiv:2512.23124v1 Announce Type: new
Abstract: Financial institutions increasingly rely on distributed architectures, open banking APIs, cloud native infrastructures, and high frequency digital transactions. These transformations expand the attack surface and expose limitations in traditional perimeter based security models. While Zero Trust architectures provide essential security principles, most existing frameworks do not explicitly incorporate transactional semantics, financial risk modeling, adaptive identity trust, or automation weighted by economic impact.
This paper introduces SecureBank, a financially aware and context adaptive Zero Trust architecture designed specifically for high assurance banking systems. The proposed framework integrates Financial Zero Trust, Adaptive Identity Scoring, Contextual Micro Segmentation, and Impact Driven Security Automation. A Monte Carlo simulation evaluates SecureBank against a representative rule based baseline architecture using metrics such as the Transactional Integrity Index (TII), Identity Trust Adaptation Level (ITAL), and Security Automation Efficiency (SAE).
The results demonstrate that SecureBank significantly improves automated attack handling and accelerates identity trust adaptation while preserving conservative and regulator aligned levels of transactional integrity. Beyond experimental validation, SecureBank is intended to serve as a reference architecture and evaluation baseline for financially aware Zero Trust systems in regulated financial environments.
Abstract: Financial institutions increasingly rely on distributed architectures, open banking APIs, cloud native infrastructures, and high frequency digital transactions. These transformations expand the attack surface and expose limitations in traditional perimeter based security models. While Zero Trust architectures provide essential security principles, most existing frameworks do not explicitly incorporate transactional semantics, financial risk modeling, adaptive identity trust, or automation weighted by economic impact.
This paper introduces SecureBank, a financially aware and context adaptive Zero Trust architecture designed specifically for high assurance banking systems. The proposed framework integrates Financial Zero Trust, Adaptive Identity Scoring, Contextual Micro Segmentation, and Impact Driven Security Automation. A Monte Carlo simulation evaluates SecureBank against a representative rule based baseline architecture using metrics such as the Transactional Integrity Index (TII), Identity Trust Adaptation Level (ITAL), and Security Automation Efficiency (SAE).
The results demonstrate that SecureBank significantly improves automated attack handling and accelerates identity trust adaptation while preserving conservative and regulator aligned levels of transactional integrity. Beyond experimental validation, SecureBank is intended to serve as a reference architecture and evaluation baseline for financially aware Zero Trust systems in regulated financial environments.
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