Communications of the ACM
Semantic integration of heterogeneous information sources
Data & Knowledge Engineering - Special issue on heterogeneous information resources need semantic access
Communication preserving protocols for secure function evaluation
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
A Proposed Architecture for Trusted Third Party Services
Proceedings of the International Conference on Cryptography: Policy and Algorithms
Information sharing across private databases
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Mapping data in peer-to-peer systems: semantics and algorithmic issues
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Analyzing and modeling encryption overhead for sensor network nodes
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
Vision paper: enabling privacy for the paranoids
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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Recent trends in the global economy force competitive enterprises to collaborate with each other to analyze markets in a better way and make decisions based on that. Therefore, they might want to share their data with each other to run data mining algorithms over the union of their data to get more accurate and representative results. During this process they do not want to reveal their data to each other due to the legal issues and competition. However, current systems do not consider privacy preservation in data sharing across private data sources. To satisfy this requirement, we propose a distributed middleware, ABACUS, to perform intersection, join, and aggregation queries over multiple private data warehouses in a privacy preserving manner. Our analytical evaluations show that ABACUS is efficient and scalable.