Predicting cost amortization for query services
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Privacy preserving query processing on secret share based data storage
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications - Volume Part I
Adjusting the trade-off between privacy guarantees and computational cost in secure hardware PIR
SDM'11 Proceedings of the 8th VLDB international conference on Secure data management
A new privacy-preserving scheme DOSPA for SaaS
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part I
A privacy-preserving join on outsourced database
ISC'11 Proceedings of the 14th international conference on Information security
A signature-based approach of correctness assurance in data outsourcing scenarios
ICISS'11 Proceedings of the 7th international conference on Information Systems Security
Security limitations of using secret sharing for data outsourcing
DBSec'12 Proceedings of the 26th Annual IFIP WG 11.3 conference on Data and Applications Security and Privacy
Query encrypted databases practically
Proceedings of the 2012 ACM conference on Computer and communications security
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Data outsourcing or database as a service is a new paradigm for data management in which a third party service provider hosts a database as a service. The service provides data management for its customers and thus obviates the need for the service user to purchase expensive hardware and software, deal with software upgrades and hire professionals for administrative and maintenance tasks. Since using an external database service promises reliable data storage at a low cost it is very attractive for companies. Such a service would also provide universal access, through the Internet to private data storedat reliable and secure sites. A client would store their data, and not need to carry their data with them as they travel. They would also not need to log remotely to their home machines, which may suffer from crashes and be unavailable. However, recent governmental legislations, competition among companies, and database thefts mandate companies to use secure and privacy preserving data management techniques. The data provider, therefore, needs to guarantee that the data is secure, be able to execute queries on the data, and the results of the queries must also be secure and not visible to the data provider. Current research has been focused only on how to index and query encrypted data. However, querying encrypted data is computationally very expensive. \emph{Providing an efficient trust mechanism} to push both database service providers and clients to behave honestly has emerged as one of the most important problem before data outsourcing to become a viable paradigm. In this paper, we describe scalable privacy preserving algorithms for data outsourcing. Instead of encryption, which is computationally expensive, we use distribution on multiple data provider sites and information theoretically proven secret sharing algorithms as the basis for privacy preserving outsourcing. The technical contributions of this paper is the establishment and development of a framework for efficient fault-tolerant scalable and theoretically secure privacy preserving data outsourcing that supports a diversity of database operations executed on different types of data, which can even leverage publicly available data sets.