دانلود Discrimination Prevention with Classification and Privacy Preservation in Data mining

Abstract

Mining of data is an important increasingly methodology for extracting and finding the meaningful hidden knowledge in huge archives of data. There are the various negative social perceptions related to mining of data, out of which many are potential discrimination and potential privacy invasion. The potential discrimination consists of unfairly treating and identifying people based on their existence and belonging to a particular group. Data mining and automated data collection techniques such as classification  and  association  rule  mining  have  provided  way  to  taking  decisions  automatically, such  as  computation  of insurance  premium,  loan  granting  or  denial,  credit  card  issue  etc.  If  the  provided  data  sets  for  training  are  biased  in discriminatory (sensitive) attributes such as, race, gender, religion, etc., discriminatory decisions can be taken and may ensue. For avoiding this situations, antidiscrimination methodology like discrimination prevention and discovery have been considered in  the  data  mining.  There  are  mainly  two  types  of  discrimination,  one  is  direct  discrimination  and  second  is  indirect discrimination. Direct discrimination exists in the situations when decisions are taken on the basis of the sensitive attributes. Indirect  discrimination  exists  in  the  situations  when  decisions  are  taken on  the basis of  the  non-sensitive  attributes  that are strongly correlated with the biased sensitive attributes.