Posted: Apr 11, 2021
The evolution of banking database administration has reached a critical juncture where traditional access control mechanisms are increasingly inadequate against sophisticated cyber threats. Conventional role-based access control (RBAC) and attribute-based access control (ABAC) systems, while foundational to banking security infrastructure, exhibit significant limitations in dynamic threat environments. These systems typically operate on static permission assignments and lack the contextual awareness necessary to adapt to emerging attack vectors. The banking sector faces unique challenges in database security, balancing stringent regulatory requirements with the need for operational efficiency and user accessibility. This research introduces a paradigm shift in banking database security through the development of a quantum-inspired, behaviorally adaptive access control framework. The novelty of our approach lies in its integration of quantum computing principles with continuous behavioral authentication, creating a system that can evaluate multiple security scenarios simultaneously and adapt in real-time to changing threat landscapes. Unlike traditional systems that rely on predefined rules and static permissions, our framework employs quantum superposition concepts to maintain multiple access possibility states until contextual factors collapse them into definitive authorization decisions. Recent advances in federated learning, as demonstrated in privacy-preserving research applications, provide inspiration for our collaborative security model improvement approach. By adapting these techniques, our system enables multiple financial institutions to collectively enhance their security models without sharing sensitive customer data or proprietary security information. This represents a significant advancement over isolated security systems that cannot benefit from collective intelligence.
Downloads: 76
Abstract Views: 2300
Rank: 45190