Paper Title
A Survey On The Approaches For Discrimination Prevention In Data Mining

Abstract
Data mining is an important technology for extracting useful patterns from large amount of data. But there are negative social perceptions about data mining, the most important ones being potential privacy invasion and potential discrimination. In data mining, discrimination is a very important issue when considering the legal and ethical aspects of privacy preservation. Most people do not have a wish to be discriminated on the basis of their race, nationality, religion, age and so on. The problem of discrimination mainly arises when these kind of attributes are used for making decisions such as giving them a job and loan. For this very reason, discovering such attributes and eliminating them from the training data without affecting their decision-making utility is essential. Beyond discrimination discovery, a more challenging issue is to prevent knowledge-based decision support systems from making discriminatory decisions. The approaches for antidiscrimination techniques are studied in this paper. Keywords—Data Mining; Discrimination Prevention; Direct and Indirect Discrimination; Anti-Discrimination.