Cloud-Based Attribute-Based Encryption and Big Data for Safeguarding Financial Data

Abstract

The potential to improve the security of financial data in the digital era is presented by the 
convergence of big data analytics, cloud computing, and attribute-based encryption (ABE). 
Innovative solutions are essential to protecting sensitive data as the banking industry battles more 
complex cyber-attacks. In order to strengthen the security of financial data, this article investigates 
the integration of ABE with big data analytics within cloud computing systems. It starts by going 
over the basics of ABE, such as ciphertext-policy ABE (CP-ABE) and key-policy ABE (KP-ABE), 
and clarifies how ABE allows for fine-grained access control over encrypted data. The paper then 
explores the use of ABE in cloud computing, highlighting its function in guaranteeing data 
scalability and confidentiality. Additionally, the integration of big data analytics with an emphasis 
on anomaly detection, predictive analytics, real-time transaction monitoring, and better security 
measures is covered in relation to financial institutions. The significance of using big data analytics 
to detect fraud, control risks, and adhere to legal obligations is emphasized in the article. To further 
illustrate the usefulness of these technologies, case studies illustrating the application of big data 
analytics and ABE in actual financial institutions are provided. Financial businesses can maintain 
legal and ethical standards while improving data security through iterative improvement and 
compliance verification. In summary, this article offers valuable perspectives on how ABE, cloud 
computing, and big data analytics may protect financial information and reduce cyber threats in 
the contemporary banking industry.