AI-Driven Cybersecurity in FinTech & Cloud: Combating Evolving Threats with Intelligent Defense Mechanisms

The increasing reliance on cloud computing in the financial technology (FinTech) sector has introduced

sophisticated cyber threats that challenge traditional security frameworks. AI-driven cybersecurity has emerged as a

transformative approach, leveraging machine learning, deep learning, and predictive analytics to enhance threat

detection, response automation, and fraud prevention. This study explores the evolving threat landscape in FinTech and

cloud security, highlighting vulnerabilities such as phishing, ransomware, API exploits, and insider threats. It examines

the role of AI-powered security mechanisms, including Zero Trust Architecture (ZTA), automated Security Information

and Event Management (SIEM) systems, and behavioral analytics, in mitigating cyber risks. Additionally, the research

addresses challenges in AI security, such as adversarial machine learning attacks, algorithmic bias, regulatory

compliance gaps, and the ethical implications of AI-driven decision-making. Future advancements, including quantum-

safe AI encryption, blockchain-integrated security frameworks, and AI-driven collaborative threat intelligence, are

analyzed for their potential to enhance cybersecurity resilience. The study concludes with recommendations for

strengthening AI-based security strategies in FinTech and cloud environments, emphasizing the importance of

transparency, regulatory alignment, and continuous innovation. By adopting AI-powered cybersecurity solutions,

financial institutions and cloud providers can proactively defend against evolving cyber threats, ensuring the integrity

and security of digital financial infrastructures.