Thursday, May 21, 2020

Privacy Protecting Confidential Information On The...

Abstract— Privacy preserving in data mining specifies the security of the confidential data or attribute in the large data base. Sharing of extracted information from a data set is beneficial to the application users. But at the same time analysing such data opens treats to privacy if not done properly. This work aims to reveal the information by protecting confidential data. In the literature various methods including Randomization, k-anonymity and data hiding have been suggested for the same. In this paper we introduce new masking technique for hiding sensitive data based on the concept of genetic algorithms. The main purpose of this method is fully supporting security of continuous numerical data in the database and keeping the utility†¦show more content†¦This usually involves using database techniques such as spatial. These patterns can then be seen as a kind of summary of the input data. In recent years, data mining has been viewed as a threat to privacy because of the widespread proliferation of electronic data maintained by [2] corporations. A number of techniques have been proposed for modifying or transforming the data in such a way so as to preserve privacy. The privacy preserving in data mining concerns the protection of confidential data from unauthorized users. The confidential data may be numerical, categorical or both. The protection of confidential data may give personal security to the workers of a company, government employers and sometimes it concerns with national security. A key problem that arises in any mass collection of data is that of confidentiality. The need for privacy preserving is sometimes due to law [3] or can be motivated by business interests. However, sharing of data can be beneficial to others and give mutual gain. A key utility of large databases today is research, whether it is scientific or economic and market oriented. For example, medical field has much to gain by pooling data for research. Despite the potential gain, this is often not possible due to the confidentiality issues which arise. So the privacy of the one’s confidential data should be preserve from other corporate or public sectors. The problem of

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