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Privacy preserving association rule mining in horizontally partitioned databases using cryptography techniques.
| Content Provider | CiteSeerX |
|---|---|
| Author | Lakshmi, N. V. Muthu K., S. Rani, Hya |
| Abstract | Abstract — Data mining techniques are used to discover hidden information from large databases. Among many data mining techniques, association rule mining is receiving more attention to the researchers to find correlations between items or items sets efficiently. In distributed database environment, the way the data is distributed plays an important role in the problem definition. The data may be distributed horizontally or vertically or in hybrid mode among different sites. There is an increasing demand for computing global association rules for the databases belongs to different sites in a way that private data is not revealed and site owner knows the global findings and their individual data only. In this paper a model is proposed which adopts a sign based secure sum cryptography technique to find global association rules with trusted party by preserving the privacy of the individual’s data when the data is distributed horizontally among different sites. fragment. Data can be partitioned in different ways such as horizontal, vertical and mixed. In horizontal partitioning of data, each fragment consists of a subset of the records of a relation R where as vertical partitioning of data, each fragment consists of a subset of attributes of a relation R. The another partitioning method is mixed fragmentation where data is partitioned horizontally and then each partitioned fragment is further partitioned into vertical fragments and vice versa [1]. Figure 1.a shows a method for mixed partitioned in which data is first partitioned vertically and then horizontally. Figure 1.b shows another mixed method in which data is partitioned horizontally and then vertically partitioned. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Different Site Privacy Preserving Association Rule Mining Individual Data Global Association Rule Important Role Vice Versa Secure Sum Cryptography Technique Vertical Fragment Partitioning Method Distributed Database Environment Site Owner Different Way Private Data Horizontal Partitioning Mixed Method Problem Definition Vertical Partitioning Many Data Mining Technique Large Database Hybrid Mode Abstract Data Mining Technique Association Rule Mining Global Finding Item Set Hidden Information Mixed Fragmentation |
| Content Type | Text |
| Resource Type | Article |
