The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Privacy preserving schema and data matching
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Privacy preserving decision tree learning over multiple parties
Data & Knowledge Engineering
Casper*: Query processing for location services without compromising privacy
ACM Transactions on Database Systems (TODS)
Formal anonymity models for efficient privacy-preserving joins
Data & Knowledge Engineering
Private record matching using differential privacy
Proceedings of the 13th International Conference on Extending Database Technology
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
Journal of Computer and System Sciences
A comprehensive framework for secure query processing on relational data in the cloud
SDM'11 Proceedings of the 8th VLDB international conference on Secure data management
Privacy preserving indexing for eHealth information networks
Proceedings of the 20th ACM international conference on Information and knowledge management
Viewpoints on emergent semantics
Journal on Data Semantics VI
Secure data management in the cloud
DNIS'11 Proceedings of the 7th international conference on Databases in Networked Information Systems
Efficient and Practical Approach for Private Record Linkage
Journal of Data and Information Quality (JDIQ)
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
Computing join aggregates over private tables
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
PrivComp: a privacy-aware data service composition system
Proceedings of the 16th International Conference on Extending Database Technology
Dividing secrets to secure data outsourcing
Information Sciences: an International Journal
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Data integration from multiple autonomous data sources has emerged as an important practical problem. The key requirement for such data integration is that owners of such data need to cooperate in a competitive landscape in most of the cases. The research challenge in developing a query processing solution is that the answers to the queries need to be provided while preserving the privacy of the data sources. In general, allowing unrestricted read access to the whole data may give rise to potential vulnerabilities as well as may have legal implications. Therefore, there is a need for privacy preserving database operations for querying data residing at different parties. In this paper, we propose a new query processing technique using third parties in a peer-to-peer system. We propose and evaluate two different protocols for various database operations. Our scheme is able to answer queries without revealing any useful information to the data sources or to the third parties. Analytical comparison of the proposed approach with other recent proposals for privacy-preserving data integration establishes the superiority of the proposed approach in terms of query response time