Advanced techniques for network disaster recovery planning in banking organizations

Posted: Jun 04, 2018

• Lucas Wilson
• Luna Brown
• Luna Flores

Abstract

The increasing complexity of banking networks and the escalating frequency of cyberattacks have exposed critical vulnerabilities in traditional disaster recovery planning methodologies. Banking organizations face unprecedented challenges in maintaining operational continuity, with network infrastructure serving as the backbone of financial transactions and customer services. Current approaches to disaster recovery planning predominantly rely on static risk assessment models and predetermined recovery procedures that fail to account for the dynamic nature of modern network threats. These conventional methods often result in suboptimal resource allocation during recovery operations and inadequate preparation for novel attack vectors. This research addresses the fundamental limitations of existing disaster recovery frameworks by introducing a quantum-inspired neural network approach that transforms recovery planning from a reactive process to a proactive resilience strategy. The methodology draws inspiration from quantum computing principles to model network states and dependencies in ways that transcend classical computational limitations. By integrating these quantum concepts with advanced neural architectures, we develop a system capable of simulating complex disaster scenarios and optimizing recovery strategies in real-time. Our approach represents a significant departure from traditional disaster recovery planning by focusing on predictive analytics and adaptive resource allocation. The system continuously learns from network telemetry and historical recovery data, enabling it to anticipate potential failure points and preemptively allocate recovery resources. This research contributes to the field by providing banking organizations with a scalable, intelligent framework that adapts to evolving network threats while maintaining the stringent security requirements of financial institutions.