Fully homomorphic encryption using ideal lattices
Proceedings of the forty-first annual ACM symposium on Theory of computing
Support Multi-version Applications in SaaS via Progressive Schema Evolution
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
The design of the force.com multitenant internet application development platform
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
A client-based privacy manager for cloud computing
Proceedings of the Fourth International ICST Conference on COMmunication System softWAre and middlewaRE
Proceedings of the First Asia-Pacific Symposium on Internetware
Privacy as a Service: Privacy-Aware Data Storage and Processing in Cloud Computing Architectures
DASC '09 Proceedings of the 2009 Eighth IEEE International Conference on Dependable, Autonomic and Secure Computing
Combining fragmentation and encryption to protect privacy in data storage
ACM Transactions on Information and System Security (TISSEC)
Fragmentation and encryption to enforce privacy in data storage
ESORICS'07 Proceedings of the 12th European conference on Research in Computer Security
Adapt: adaptive database schema design for multi-tenant applications
Proceedings of the 21st ACM international conference on Information and knowledge management
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In cloud computing, multi-tenancy applications utilize shared resources to serve multi tenants through "single instance multi-tenancy". Applications and databases are both deployed at the platform of untrusted service providers. Data privacy has become the biggest challenges in wider adoption of cloud computing. Specifically, data schema evolves due to ondemand customization in cloud computing. How to protect the data privacy during data schema evolution for multi-tenancy application is an interesting and important problem. We proposed the privacy requirements for data schema evolution based on the data combination privacy, and then represented the data privacy-preserving architecture. A data schema evolution graph is constructed, and then the privacy-preserving evolution path is searched based on the principle of privacy requirements consistency. Analysis and experiments demonstrate the corrective and effective of the data privacy preservation approach during data schema evolution in cloud computing.