Aris Gkoulalas-Divanis, Vassilios S. Verykios Association Rule Hiding for Data Mining

Annotation

Privacy and security risks arising from the application of different data miningtechniques to large institutional data repositories have been solely investigated by anew research domain, the so-called privacy preserving data mining. Association rulehiding is a new technique on data mining, which studies the problem of hiding sensitiveassociation rules from within the data. Association Rule Hiding for Data Mining addresses the optimization problem of"hiding" sensitive association rules which due to its combinatorial nature admitsa number of heuristic solutions that will be proposed and presented in this book. Exact solutions of increased time complexity that have been proposed recently arealso presented as well as a number of computationally efficient (parallel) approachesthat alleviate time complexity problems, along with a discussion regarding unsolvedproblems and future directions. Specific examples are provided throughout this bookto help the reader study, assimilate and appreciate the important aspects of this challengingproblem. Association Rule Hiding for Data Mining is designed for researchers, professorsand advanced-level students in computer science studying privacy preserving datamining, association rule mining, and data mining. This book is also suitable forpractitioners working in this industry.