Sap Se

Stephan Kessler

Kai Morich

Thomas Seufert

Christian Mathis

Youssef Hatem

Taehun Kim

Taehyung Lee

Jin Uk Bae

Chuho Chang

Kaweh Amoi-Taleghani

Kornel Skalkowski

Axel Christ

Jens Hoff

Maike Jansen

Raik Kulinna

In an example embodiment, using several computerized innovative data anonymization techniques, sensitive and personal data can be anonymized so that it can be used in further analysis without revealing the individuals to which the data applies. More particularly, a privacy view is created for a microdata table by generating one or more transformations, based on an anonymization method. Only once a request for data in the microdata table is received from a data consumer is the privacy view populated or repopulated with the most recent data from the microdata table by transforming it using the one or more transformations.

Privacy-aware service data management

Implementations of the present disclosure include receiving a view command for creating a view to display anonymized data in response to one or more queries, the view command including a view name, a table, a set of columns of the table, an anonymization type, a set of static parameters, and, for a sub-set of columns of the table, one or more sets of column-specific parameters, each set of column-specific parameters being specific to anonymization of data of a respective column of the table included in the sub-set of columns, storing the view command within the database system, and receiving a query referencing the view, and in response, providing a data set including data from each column in the sub-set of columns, receiving an anonymized data set including anonymized data that is generated from the data set using the anonymization type, the static parameters, and the sets of column-specific parameters.

Data anonymization in database management systems

Techniques are described for real time anonymization. In one example, a first a first query associated with a table is received, the table associated with a first anonymization operation satisfying satisfies a privacy requirement. The first anonymization operation is applied at runtime to generate a first anonymized data set against which the first query is executed. At Tafter T, a subsequent query is received. A determination is made as to whether a change to the table has occurred since T. If so, a determination is made as to whether the first anonymization operation satisfies the privacy requirement as applied to the current table. If the operation does not satisfy the privacy requirement when applied to the current table, a second anonymization operation satisfying the defined privacy requirement is determined and applied at runtime to generate a second anonymized data set against which the subsequent query can be executed.

Real-time anonymization

Techniques are described for identifying changes to databases. In one example, a table associated with a data set is identified containing at least one entry, each entry associated with a sequence column value. The sequence column value for new entries is automatically incremented by one from a last max value. At time T, a total entry count and a maximum sequence column value of the entries is calculated and stored in metadata. At time Tlater than T, a total entry count and a maximum sequence column value in the table is calculated and compared to the previously stored values. If the values are the same, the table has not changed; if the values are different, then a change has been made. In response to a determined change, the calculated total entry count and the maximum sequence column value at Tis stored in the metadata.

Database independent detection of data changes

In one respect, there is provided a distributed database system that includes hosts configured to store and/or manage data, a first query processing engine comprising a master node and an executor node, and a second query processing engine. The master node can be implemented on programmable processors and configured to perform operations. The operations can include: offloading, to the second query processing engine, a creation of a first and a second table such that the first and the second table are partitioned by the second query processing engine; generating an execution plan for a query on data in the distributed database system, the execution plan including a distributed join operation that combines data from the first and second table; determining to push down, to the second query processing engine, the distributed join operation; and dispatching, to the executor node, a portion of the execution plan including the distributed join operation.

Distributed joins in a distributed database system

In one respect, there is provided a distributed database system. The distributed database system can include a plurality of hosts configured to store and/or manage data, a first query processing engine comprising a master node and an executor node, and a second query processing engine. The master node can be implemented on one or more programmable processors and configured to perform operations. The operations can include: generating an execution plan for a query on data that is stored at and/or managed by one or more of the plurality of hosts; determining to push down, to the second query processing engine, at least one data processing operations in the execution plan; and dispatching, to the executor node, at least a portion of the execution plan, the portion of the execution plan including the at least one data processing operation that is pushed down to the second query processing engine.

Growing community of inventors

Linkenheim-Hochstetten, Germany

Stephan Kessler