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 6 Distrib Parallel Databases (2009) 25: 5-28 gregates to data warehouses for OLAP purposes, and reveal exactly what is desired, neither more nor less. We call this functionality "revelation on demand".
Imagine that you have been entrusted with private data, such as corporate product information, sensitive government information, or symptom and treatment information about hospital patients. You may want to issue queries whose result will combine private and public data, but private data must not be revealed. GhostDB is an architecture and system to achieve this. You carry private data in a smart USB key (a large Flash persistent store combined with a tamper and snoop-resistant CPU and small RAM). When the key is plugged in, you can issue queries that link private and public data and be sure that the only information revealed to a potential spy is which queries you pose. Queries linking public and private data entail novel distributed processing techniques on extremely unequal devices (standard computer and smart USB key). This paper presents the basic framework to make this all work intuitively and efficiently.
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