Executing SQL over encrypted data in the database-service-provider model
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Securing XML Documents with Author-X
IEEE Internet Computing
Transforming data to satisfy privacy constraints
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Practical Techniques for Searches on Encrypted Data
SP '00 Proceedings of the 2000 IEEE Symposium on Security and Privacy
Top-Down Specialization for Information and Privacy Preservation
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Data Privacy through Optimal k-Anonymization
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Plutus: Scalable Secure File Sharing on Untrusted Storage
FAST '03 Proceedings of the 2nd USENIX Conference on File and Storage Technologies
Trustworthy keyword search for regulatory-compliant records retention
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
A security model for full-text file system search in multi-user environments
FAST'05 Proceedings of the 4th conference on USENIX Conference on File and Storage Technologies - Volume 4
Confidentiality-preserving rank-ordered search
Proceedings of the 2007 ACM workshop on Storage security and survivability
Controlling access to published data using cryptography
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Privacy-preserving indexing of documents on the network
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Zerber: r-confidential indexing for distributed documents
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking
Proceedings of the 8th ACM SIGSAC symposium on Information, computer and communications security
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Privacy-preserving document exchange among collaboration groups in an enterprise as well as across enterprises requires techniques for sharing and search of access-controlled information through largely untrusted servers. In these settings search systems need to provide confidentiality guarantees for shared information while offering IR properties comparable to the ordinary search engines. Top-k is a standard IR technique which enables fast query execution on very large indexes and makes systems highly scalable. However, indexing access-controlled information for top-k retrieval is a challenging task due to the sensitivity of the term statistics used for ranking. In this paper we present Zerber+R -- a ranking model which allows for privacy-preserving top-k retrieval from an outsourced inverted index. We propose a relevance score transformation function which makes relevance scores of different terms indistinguishable, such that even if stored on an untrusted server they do not reveal information about the indexed data. Experiments on two real-world data sets show that Zerber+R makes economical usage of bandwidth and offers retrieval properties comparable with an ordinary inverted index.