Privacy Preservation in Information System

Privacy Preservation in Information System

D. P. Acharjya (VIT University, India) and Geetha Mary A. (VIT University, India)
Copyright: © 2014 |Pages: 24
DOI: 10.4018/978-1-4666-4940-8.ch003
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The information technology revolution has brought drastic change in the way data is collected or generated for decision mining. The accumulated data has no relevance unless it provides certain useful information pertaining to the interest of an organization. The real challenge lies in converting high dimensional data into knowledge and to use this knowledge for the development of the organization. On the other hand, hiding an organization’s sensitive information is a major concern. Much research has been carried out in this direction. This chapter discusses various privacy preservation techniques that can be employed in an information system to safeguard the sensitive information of an organization. This chapter also highlights sensitive fuzzy association rules that can be generated from an information system. The authors provide illustrations wherever necessary to give a clear idea of the concepts developed.
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Information System

The basic objective of inductive learning and data mining is to learn the knowledge for classification. However, in real world problems, we may not be faced with simply classification. One such problem is the ordering of objects. On the contrary, we are interested in hiding sensitive associations that is present in an information system. Before we discuss, various privacy preservation techniques to hide sensitive associations, one must know about an information system. An information system contains a finite set of objects typically represented by their values on a finite set of attributes. Such information system may be conveniently described in a tabular form in which each row represents an object whereas each column represents an attribute. Each cell of the information system contains an attribute value. Now, we define formally an information system as below.

An information system is defined as a quadruple where is a finite nonempty set of objects called the universe, is a finite nonempty set of attributes, is a nonempty set of values for , is an information function. For example, consider a sample information system as presented in Table 1 in which represents a nonempty finite set of objects; and A = {Humidity, Windy, Temperature} be a finite set of attributes. The information system presented in Table 1 is a qualitative system, where all the attribute values are discrete and categorical (qualitative).

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