Sap Se

Patrick Grofig

Florian Kerschbaum

Martin Haerterich

Axel Schroepfer

Andreas Schaad

Mathias Kohler

Walter Tighzert

Isabelle Hang

Methods, systems, and computer-readable storage media for optimizing query processing in encrypted databases. In some implementations, actions include receiving a query that is to be used to query an encrypted database, generating a plurality of query plans based on the query, each query plan including a local query and one or more remote queries, the local query being executable at a client-side and the one or more remote queries being executable at a server-side, selecting an optimal query plan from the plurality of query plans, providing one or more remote queries of the optimal query plan to the server-side for execution, receiving one or more remote results, and processing a local query of the optimal query plan and the one or more remote results to provide a final query result.

Local versus remote optimization in encrypted query processing

Methods, systems, and computer-readable storage media for selecting columns for re-encryption in join operations. In some implementations, actions include determining a first column and a second column to be joined, receiving a first key corresponding to the first column and a second key corresponding to the second column, receiving a first rank associated with the first key and a second rank associated with the second key, selecting the second column for re-encryption based on the first rank and the second rank, and providing the first column, the second column, and the first key for performing a join operation, the second column being re-encrypted based on the first key.

Optimal re-encryption strategy for joins in encrypted databases

Embodiments relate to processing encrypted data, and in particular to identifying an appropriate layer of encryption useful for processing a query. Such identification (also known as the onion selection problem) is achieved utilizing an adjustable onion encryption procedure. Based upon defined requirements of policy configuration, alternative resolution, and conflict resolution, the adjustable onion encryption procedure entails translating a query comprising an expression in a database language (e.g. SQL) into an equivalent query on encrypted data. The onion may be configured in almost arbitrary ways directing the onion selection. An execution function introduces an execution split to allow local (e.g. client-side) query fulfillment that may otherwise not be possible in a secure manner on the server-side. A searchable encryption function may also be employed, and embodiments accommodate aggregation via homomorphic encryption. Embodiments may be implemented as an in-memory column store database system.

Encrypted in-memory column-store

Embodiments provide ideal security, order-preserving encryption (OPE) of data of average complexity, thereby allowing processing of the encrypted data (e.g. at a database server in response to received queries). Particular embodiments achieve high encryption efficiency by processing plaintext in the order preserved by an existing compression dictionary already available to a database. Encryption is based upon use of a binary search tree of n nodes, to construct an order-preserving encryption scheme having &#x3a9;(n) complexity and even O(n), in the average case. A probability of computationally intensive updating (which renders conventional OPE impractical for ideal security) is substantially reduced by leveraging the demonstrated tendency of a height of the binary search tree to be tightly centered around O(log n). An embodiment utilizing such an encryption scheme is described in the context of a column-store, in-memory database architecture comprising n elements. OPE according to embodiments is compatible with adjustable encryption approaches.

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Karlsruhe, Germany

Patrick Grofig