A Generative AI Approach for Ensuring Data Integrity Security Resilience in Fintech Systems

被引:0
作者
Chatterjee, Pushpita [1 ]
Das, Debashis [2 ]
Rawat, Danda B. [1 ]
机构
[1] Howard Univ, Dept EE&CS, Washington, DC 20059 USA
[2] Meharry Med Coll, Dept CS&DS, Nashville, TN USA
来源
2024 IEEE 24TH INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND INTERNET COMPUTING WORKSHOPS, CCGRIDW 2024 | 2024年
关键词
Fintech; Data Integrity; Security; Resilience; Generative Artificial Intelligence; Machine Learning; Cybersecurity;
D O I
10.1109/CCGridW63211.2024.00027
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The Fintech industry represents the convergence of finance and technology through innovative digital solutions from mobile banking to cryptocurrency. However, it faces big challenges with keeping data safe and systems strong. Traditional methods struggle to keep pace with sophisticated threats and complexities inherent in modern Fintech ecosystems. This paper proposes an approach to address these challenges using Generative AI and blockchain integration to make Fintech systems more resilient. Advanced machine learning algorithms detect and prevent data tampering in the proposed systems. Generative AI is used for threat detection, anomaly recognition, and real-time monitoring in system security. Then, we integrate blockchain technology to enhance the overall resilience of systems. Blockchain technology enhances the reliability of financial services in secure transactions, validating blocks, and distributing control across decentralized networks. These combined methodologies address the critical challenges of data integrity, security, and system resilience in dynamic Fintech systems. The performance analysis demonstrates the efficacy of our proposed framework in enhancing data integrity, security measures, and system resilience within Fintech systems.
引用
收藏
页码:168 / 173
页数:6
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