Advancing Cloud Security in Digital Finance: AI-Driven Threat Detection, Cryptographic Solutions, and Privacy Challenges

21 Pages Posted: 5 Mar 2025 The University of Tampa Date Written: February 13, 2025 This study examines security risks, emerging technologies, and cryptographic techniques in cloudbased digital currency transactions using a quantitative research approach. Data was sourced from the REKT Database, Web3 Security Report, and Elliptic Open Dataset, employing descriptive statistical analysis, regression modeling, and time-series analysis to assess security vulnerabilities, fraud reduction trends, and regulatory compliance effectiveness. Findings reveal that AI-driven security measures reduced fraud cases by 55% from 2022 to 2025, while illicit transactions declined from 12.5% in 2019 to 6.1% in 2023, demonstrating the impact of cryptographic advancements and regulatory interventions. However, cybercriminals are shifting toward highvalue, precision-based attacks, necessitating an integrated security framework. This study contributes to AI-driven security, cryptographic resilience, and regulatory compliance in cloud Keywords: Cloud security, AI fraud detection, quantum cryptography, cryptocurrency regulation, digital financial security Suggested Citation: Suggested Citation Cybersecurity & Data Privacy Law & Policy eJournal Subscribe to this free journal for more curated articles on this topic