Title :
Synthetic Data Generation Capabilties for Testing Data Mining Tools
Author :
Jeske, Daniel R. ; Lin, Pengyue J. ; Rendon, Carlos ; Xiao, Rui ; Samadi, Behrokh
Author_Institution :
California Univ., Riverside, CA
Abstract :
Recently, 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 (i) lack of sufficient specific knowledge on what to look for, (ii) 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. The original applications for this platform were people information and credit card transaction data sets. In this paper, we introduce a new shipping container application that can support the testing of data mining tools developed for port security
Keywords :
data mining; freight containers; marine engineering; security of data; ships; data mining tool; security application; shipping container application; synthetic data generation; Costs; Credit cards; Data mining; Data security; Databases; Information security; Privacy; Prototypes; Research and development; Testing; Knowledge Discovery and Data Mining; Semantic Graphs; Shipping Container; Synthetic Data Generation;
Conference_Titel :
Military Communications Conference, 2006. MILCOM 2006. IEEE
Conference_Location :
Washington, DC
Print_ISBN :
1-4244-0617-X
Electronic_ISBN :
1-4244-0618-8
DOI :
10.1109/MILCOM.2006.302440
