| Publisher | University of California | ||
|---|---|---|---|
| Format | 199.4KB PDF | Date added | 01 Jun 2006 |
| Topics | Data Mining - Analysis, Application Development | ||
| Downloads | 14 | ||
Due to commercial success of data mining tools, there has been much attention to extracting hidden information from large databases to predict security problems and terrorist threats. The security applications are somewhat more complicated than commercial applications due to lack of sufficient specific knowledge on what to look for and R&D labs developing these tools are not able to easily obtain sensitive information due to security, privacy or cost issues. Tools developed for security applications require substantially more testing and revisions in order to prevent costly errors. This paper describes a platform for the generation of realistic synthetic data that can facilitate the development and testing of data mining tools.
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