AI-Driven Cloud Banking Security: Integrating Deep Learning, NLP, Governance, and Citrix-Enhanced Protection with Sign Language Interpretation
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Abstract
The rapid evolution of cloud-native banking demands robust, inclusive, and intelligent security mechanisms to counter emerging digital threats while ensuring accessibility and governance compliance. This research proposes an AI-driven cloud banking security framework that integrates Deep Learning, Natural Language Processing (NLP), and governance analytics for real-time threat detection, data privacy, and regulatory alignment. The model leverages Citrix-enhanced virtualization and endpoint protection to strengthen multi-layered defense across distributed environments. Additionally, Sign Language Interpretation (SLI) is embedded through AI-based recognition and translation modules, enabling inclusive access and secure communication for hearing-impaired users. Experimental results demonstrate improved detection accuracy, faster incident response, and enhanced user accessibility in financial ecosystems. The proposed architecture emphasizes a balanced approach combining AI automation, risk governance, and accessibility innovation to build trust and transparency in cloud-native digital banking systems.
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