Security-Performance Optimization in Cloud-Based Bank Data Processing Using HE-ZKP-ORAM

Abstract

In the context of banking systems increasingly relying on cloud computing platforms, protecting sensitive data while maintaining processing performance is a major challenge. This paper presents and evaluates a cloud banking data processing model that integrates Homomorphic Encryption (HE), Zero-Knowledge Proof (ZKP), and the ORAM protocol to achieve a balance between security and performance. Experiments were conducted on a real Bank Marketing (UCI) dataset with 5000 records, using DSL query operations to calculate the average balance, count high-balance customers, total call duration, and savings deposit acceptance rate. The results show that the combination of HE, ZKP, and ORAM significantly improves security but increases computational cost; however, a suitable configuration can significantly reduce latency while still meeting security requirements. A detailed analysis of the security-performance trade-off provides an important empirical basis for implementing banking data security solutions in the cloud.