A Novel Multi-Secret Sharing Approach for Secure Data Warehousing and On-Line Analysis Processing in the Cloud
This addresses data privacy, integrity, and availability issues for organizations using cloud data warehousing, but it appears incremental as it builds upon existing secret sharing techniques.
The paper tackles the security concerns of storing sensitive data in cloud-based data warehouses and on-line analytical processing by proposing a new multi-secret sharing approach, which is validated theoretically and experimentally, showing superiority over related methods.
Cloud computing helps reduce costs, increase business agility and deploy solutions with a high return on investment for many types of applications, including data warehouses and on-line analytical processing. However, storing and transferring sensitive data into the cloud raises legitimate security concerns. In this paper, we propose a new multi-secret sharing approach for deploying data warehouses in the cloud and allowing on-line analysis processing, while enforcing data privacy, integrity and availability. We first validate the relevance of our approach theoretically and then experimentally with both a simple random dataset and the Star Schema Benchmark. We also demonstrate its superiority to related methods.