Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Executing SQL over encrypted data in the database-service-provider model
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Providing Database as a Service
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Modeling and assessing inference exposure in encrypted databases
ACM Transactions on Information and System Security (TISSEC)
Journal of Cognitive Neuroscience
Preserving data privacy in outsourcing data aggregation services
ACM Transactions on Internet Technology (TOIT) - Special Issue on the Internet and Outsourcing
Fragmentation Design for Efficient Query Execution over Sensitive Distributed Databases
ICDCS '09 Proceedings of the 2009 29th IEEE International Conference on Distributed Computing Systems
Enforcing Confidentiality Constraints on Sensitive Databases with Lightweight Trusted Clients
Proceedings of the 23rd Annual IFIP WG 11.3 Working Conference on Data and Applications Security XXIII
Data protection in outsourcing scenarios: issues and directions
ASIACCS '10 Proceedings of the 5th ACM Symposium on Information, Computer and Communications Security
Combining fragmentation and encryption to protect privacy in data storage
ACM Transactions on Information and System Security (TISSEC)
Keep a few: outsourcing data while maintaining confidentiality
ESORICS'09 Proceedings of the 14th European conference on Research in computer security
An OBDD approach to enforce confidentiality and visibility constraints in data publishing
Journal of Computer Security - DBSec 2011
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Data outsourcing provides companies a cost effective method for their data to be stored, managed, and maintained by a third-party. Data outsourcing offers many economical benefits, but also introduces several privacy concerns. Many solutions have been proposed for maintaining privacy while outsourcing data in the data as plain-text model. We propose a method that can maintain a similar level of privacy while improving upon the query performance of previous solutions. The motivating principle behind our solution is that if the data owner possesses a small amount of secure local storage, it can be used as a pseudoindex table to improve query performance for selection queries involving conjunctions. We offer a heuristic approach for calculating the required storage resources and provide experimental analysis of the scheme.