Computational Improvements in Parallelized K-Anonymous Microaggregation of Large Databases
The technical contents of this paper fall within the field of statistical disclosure control (SDC), which concerns the postprocessing of the demographic portion of the statistical results of surveys containing sensitive personal information, in order to effectively safeguard the anonymity of the par...
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| creator | Mohamad Mezher, Ahmad Garcia Alvarez, Alejandro Rebollo-Monedero, David Forne, Jordi |
| description | The technical contents of this paper fall within the field of statistical disclosure control (SDC), which concerns the postprocessing of the demographic portion of the statistical results of surveys containing sensitive personal information, in order to effectively safeguard the anonymity of the participating respondents. The concrete purpose of this study is to improve the efficiency of a widely used algorithm for k-anonymous microaggregation, known as maximum distance to average vector (MDAV), to vastly accelerate its execution without affecting its excellent functional performance with respect to competing methods. The improvements put forth in this paper encompass algebraic modifications and the use of the basic linear algebra subprograms (BLAS) library, for the efficient parallel computation of MDAV on CPU. |
| doi_str_mv | 10.1109/ICDCSW.2017.43 |
| format | Conference Proceeding |
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| identifier | EISSN: 2332-5666 |
| ispartof | 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW), 2017, p.258-264 |
| issn | 2332-5666 |
| language | eng |
| recordid | cdi_csuc_recercat_oai_recercat_cat_2072_303069 |
| source | Recercat |
| subjects | algebraic modifications Algorithm design and analysis Bases de dades BLAS library C++ languages CPU Data privacy Database management Distortion Enginyeria de la telecomunicació Gestió k-Anonymity large databases Libraries Linear algebra linear algebra subprograms maximum distance to average vector MDAV Microaggregation parallel computation Parallelization parallelized k-anonymous microaggregation Partitioning algorithms sensitive personal information statistical disclosure control Àrees temàtiques de la UPC |
| title | Computational Improvements in Parallelized K-Anonymous Microaggregation of Large Databases |
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