ACM Transactions on Database Systems (TODS)
Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
Multi-table joins through bitmapped join indices
ACM SIGMOD Record
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Executing SQL over encrypted data in the database-service-provider model
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Efficient execution of joins in a star schema
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Hashing Methods and Relational Algebra Operations
VLDB '84 Proceedings of the 10th International Conference on Very Large Data Bases
iButton Enrolment and Verification Requirements for the Pressure Sequence Smartcard Biometric
E-SMART '01 Proceedings of the International Conference on Research in Smart Cards: Smart Card Programming and Security
The VLDB Journal — The International Journal on Very Large Data Bases
Sing the truth about ad hoc join costs
The VLDB Journal — The International Journal on Very Large Data Bases
PicoDBMS: Scaling down database techniques for the smartcard
The VLDB Journal — The International Journal on Very Large Data Bases
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Logical and physical design issues for smart card databases
ACM Transactions on Information Systems (TOIS)
Balancing confidentiality and efficiency in untrusted relational DBMSs
Proceedings of the 10th ACM conference on Computer and communications security
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
GhostDB: querying visible and hidden data without leaks
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
GnatDb: a small-footprint, secure database system
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Memory requirements for query execution in highly constrained devices
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Data degradation: making private data less sensitive over time
Proceedings of the 17th ACM conference on Information and knowledge management
Cardinality estimation and dynamic length adaptation for Bloom filters
Distributed and Parallel Databases
MILo-DB: a personal, secure and portable database machine
Distributed and Parallel Databases
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Private data sometimes must be made public. A corporation may keep its customer sales data secret, but reveals totals by sector for marketing reasons. A hospital keeps individual patient data secret, but might reveal outcome information about the treatment of particular illnesses over time to support epidemiological studies. In these and many other situations, aggregate data or partial data is revealed, but other data remains private. Moreover, the aggregate data may depend not only on private data but on public data as well, e.g. commodity prices, general health statistics. Our GhostDB platform allows queries that combine private and public data, produce aggregates to data warehouses for OLAP purposes, and reveal exactly what is desired, neither more nor less. We call this functionality "revelation on demand".