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Design of an Inference Control Process in OLAP Data Cubes

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2009, 14(5), pp.183-193
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

이덕성 1 CHOI IN SOO 1

1숭실대학교

Accredited

ABSTRACT

Both On-Line Analytical Processing (OLAP) data cubes and Statistical Databases (SDBs) deal with multidimensional data sets, and both are concerned with statistical summarizations over the dimensions of the data sets. However, there is a distinction between the two that can be made. While SDBs are usually derived from other base data, OLAP data cubes often represent directly the base data. In other word, the base data of SDBs are the macro-data, whereas the core cubiod data in OLAP data cubes are the micro-data. The base table in OLAP is used to populate the data cube with values of the measure attribute, and each record in the base tables is used to populate a cell of the core cuboid. The fact that OLAP data cubes mostly represent the micro-data may make some records be absent in the base table. Some cells of the core cuboid remain empty, if corresponding records are absent in the base table. Wang and others proposed a method for securing OLAP data cubes against privacy breaches. They assert that the proposed method does not depend on specific types of aggregation functions. In this paper, however, it is found that their assertion on aggregate functions is wrong whenever any cell of the core cuboid remains empty. The objective of this study is to design an inference control process in OLAP data cubes which rectifying Wang's error.

Citation status

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