Flexible authentication of XML documents
CCS '01 Proceedings of the 8th ACM conference on Computer and Communications Security
CRYPTO '89 Proceedings of the 9th Annual International Cryptology Conference on Advances in Cryptology
Authentic data publication over the internet
Journal of Computer Security - IFIP 2000
Providing Database as a Service
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Authenticating Query Results in Edge Computing
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Privacy preserving mining of association rules
Information Systems - Knowledge discovery and data mining (KDD 2002)
Privacy-Preserving Distributed Mining of Association Rules on Horizontally Partitioned Data
IEEE Transactions on Knowledge and Data Engineering
Tamper detection in audit logs
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Vision paper: enabling privacy for the paranoids
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
A privacy-preserving index for range queries
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Query racing: fast completeness certification of query results
DBSec'10 Proceedings of the 24th annual IFIP WG 11.3 working conference on Data and applications security and privacy
Authenticated Index Structures for Aggregation Queries
ACM Transactions on Information and System Security (TISSEC)
CorrectDB: SQL engine with practical query authentication
Proceedings of the VLDB Endowment
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In this paper we address the problem of ensuring the correctness of query results returned by an untrusted private database. The database owns the data and may modify it at any time. The querier is allowed to execute queries over this database; however it may not learn anything more than the result of these legal queries. The querier does not necessarily trust the database and would like the owner to furnish proof that the data has not been modified in response to recent events such as the submission of the query. We develop two metrics that capture the correctness of query answers and propose a range of solutions that provide a trade-off between the degree of exposure of private data, and the overhead of generation and verification of the proof. Our proposed solutions are tested on real data through implementation using PostgreSQL.