Privacy Preserving Data Mining (Advances in Information Security)

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Product Description

Privacy preserving data mining implies the "mining" of knowledge from distributed data without violating the privacy of the individual/corporations involved in contributing the data. This volume provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. Crystallizing much of the underlying foundation, the book aims to inspire further research in this new and growing area.

Privacy Preserving Data Mining is intended to be accessible to industry practitioners and policy makers, to help inform future decision making and legislation, and to serve as a useful technical reference.

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Privacy Preserving Data Mining (Advances in Information Security) Review

Privacy is very important for any data manipulation and data mining gives the feeling to the large public to have the power to discover very private things in data. And it's true.

The authors try to find some methods to do data mining in avoiding of having access to the private part (too much private part) of these data but in staying able to learn something about individuals behind. It's not easy and very interesting to learn.

Of course the applications are limited because very often data mining has for purpose to score a particular individual.

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