CCBPS: A Hardware-based Data Loss Prevention Approach

As an important asset of financial enterprises, it is crucial to ensure the completeness and availability of data in financial Information Technology (IT) systems. Cross-regional, multi-data center geographical disaster recovery architecture design is the current mainstream approach in which, during a regional disaster, the data in transmission will be lost due to lack of backups. In this paper, we propose a hardware-based data loss prevention approach, called Critical Core Backup and Protection System (CCBPS). By reliably storing the asynchronous data on backup storage devices, the disaster recovery and complete data retrieval capabilities of the system are enhanced. The verification results show that the proposed method achieves zero data loss capability and the assessment results show that higher data availability is reached compared to the common geographical disaster recovery method.

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Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/issrew63542.2024.00043
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
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article

CCBPS: A Hardware-based Data Loss Prevention Approach

Yufei Yang, Panshi Jin, Lei Xing, Hao Zhou
Parallel Computing and Optimization Techniques
article

CCBPS: A Hardware-based Data Loss Prevention Approach

Yufei Yang, Panshi Jin, Lei Xing, Hao Zhou
article en

Abstract

As an important asset of financial enterprises, it is crucial to ensure the completeness and availability of data in financial Information Technology (IT) systems. Cross-regional, multi-data center geographical disaster recovery architecture design is the current mainstream approach in which, during a regional disaster, the data in transmission will be lost due to lack of backups. In this paper, we propose a hardware-based data loss prevention approach, called Critical Core Backup and Protection System (CCBPS). By reliably storing the asynchronous data on backup storage devices, the disaster recovery and complete data retrieval capabilities of the system are enhanced. The verification results show that the proposed method achieves zero data loss capability and the assessment results show that higher data availability is reached compared to the common geographical disaster recovery method.

Huawei Technologies (China) (CN), China Construction Bank (CN)
Openalex Percentile: Top 77%
Parallel Computing and Optimization Techniques
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