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11.6 Conclusion
In this chapter, we review the existing Privacy-preserving Data Mining methods.
General knowledge and understanding of these methods and techniques is highly
relevant for preventing discriminatory effects of modern data mining techniques.
When appropriate, we have underscored the usability of specific techniques to
prevent discriminatory use of data mining. Some of the techniques presented in
this chapter generalize the data, so that any stigmatized group would not be more
targeted in the generalized data than it is in the general population. All data gene-
ralizations, however, incur a cost in data quality. The cryptographic approaches,
on the other hand, preserve the data but impose a heavy computational overhead.
The chapter is complete with a discussion of some of the challenges before PPDM
as a field.
Acknowledgments. Research support by the Natural Sciences and Engineering Research
Council of Canada and the Ontario Centres of Excellence is kindly acknowledged by the
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