International Business Machines Corporation

David Kelly

Pedro Miguel Barbas

Enzo Cialini

Clara Liu

Manohar Bashyam

Martin J Neary

Jan Mahon

Qinlong Luo

Johnson Uman

Donald Fraser

A method of accessing objects with fine-grained access control (FGAC) in a relational database management system (RDBMS) storing a segmented column-major database. For each object with access restrictions, an artificial neural network (ANN), is trained by generating an equally distributed segment map of segmented data entries, so that the map reproduces the row disposition in the unsegmented object. When a user access request is received, these ANNs are referred to determine if any of the objects to be accessed are subject to access restrictions. If that is the case, then the ANN creates a pseudo-view construct of its associated object which is limited to data entries that the user has permission to access. The pseudo-views are then injected into the user access request to embed the fine-grained access controls for subsequent processing of the request, which can then proceed without further regard to user-specific access restrictions.

Fine-grained access control of column-major relational database management systems

Concepts for processing a SQL statement comprising a ROLAP sort operation are presented. One such concept comprises: determining whether a ROLAP partitioning column of the SQL statement does not refer to database columns from a sort operation of the SQL statement; and determining whether the ROLAP partitioning columns of the SQL statement are all referenced in the output of the SQL statement. Responsive to determining a ROLAP partitioning column of the SQL statement does not refer to database columns from a sort operation of the SQL statement, and to determining all of the ROLAP partitioning columns of the SQL statement are referenced in the output of the SQL statement, the SQL statement is modified by removing the ROLAP sort operation from the SQL statement.

Optimizing relational online analytical processing sort operations

Embodiments of the present invention provide systems and methods for associating rule mining in data comprising first and second variables, by generating a first and second filtering bitmap. The first filtering bitmap represents a set of values for the second variable for each of a plurality of values of the first variable. The second filtering bitmap represents, associations between frequent values of the second variable, which enables the identification of frequent 2-pattern itemsets. Thus, by performing first logical operations on the frequent 2-pattern itemsets, frequent high order-pattern itemsets may be identified. A max pattern itemset may be identified among the frequent high order-pattern itemsets. As a result, embodiments may mitigate performance and stability problems associated with conventional association rule mining approaches.

Association rule mining using max pattern transactions

Embodiments of the present invention provide systems and methods for associating rule mining. By way of example, embodiments obviate or mitigate performance and stability problems associated with conventional association rule mining approaches, by proposing concepts implementing association rule mining using rolling filtering bitmaps over dynamic data.

Association rule mining

A method, system and computer program for implementing fine-grained access control (FGAC) of data stored in a dataset. In response to receiving a data query statement from a user, any representational index exclusions that are relevant to the data query statement are identified, wherein each index exclusion specifies an access restriction to the data. It is then determined whether any of the identified representational index exclusions are to be applied to the data query statement, and if 'yes' then the data query statement is modified before being processed, so that processing of the query takes place by searching the dataset under restriction of the representational index exclusions. The proposed approach allows for easy creation and modification of FGAC privacy rules without introducing performance gaps in processing the data query statements.

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Robertstown, Ireland

David Kelly