24-08-2012, 11:12 AM
Data Mining
Abstact DataMining.doc (Size: 27 KB / Downloads: 31)
ABSTRACT
Data mining is the analyzing and extraction of different perspective and summarizes information from large database. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.
Data mining contains the secured information such as financial and healthcare records. To handle such large private database with, data mining algorithms with privacy is required. The privacy preserving becomes important concern when we dealing security related data. Data perturbation is one of the well known methods for avoiding such kinds of privacy leakage. The objective of data perturbation method is to distort the individual data values while preserving the underlying statistical distribution properties. These data perturbation methods are assessed in terms of both their privacy parameters as well as its associated utility measure. Privacy parameters are used to measure the degree of privacy protection while data utility measures assess whether the dataset keeps the performance of data mining techniques after the data distortion.
Privacy preservation is a major concern in the application of data mining techniques to counterterrorism and homeland security. Data distortion is a critical component to preserve privacy in security-related data mining applications. We propose a Fast Fourier Transform (FFT) based method for data distortion, and compare it with the Singular Value Decomposition (SVD) based method
My research aims to develop a unified data description and understanding framework to enable discovery of useful knowledge and events from data sets related to international, homeland, or other types of security so to explore this, we have developed a Java data-mining program that collects statements of security-related statistics from the World Wide Web.