Association Rule Hiding for Data Mining 2010th Edition by Aris Gkoulalas Divanis, Vassilios Verykios ISBN 1441965688 9781441965684

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Product details:

ISBN 10:       1441965688
ISBN 13: 978-1441965684
Author:         Aris Gkoulalas-Divanis, Vassilios S. Verykios

Privacy and security risks arising from the application of different data mining techniques to large institutional data repositories have been solely investigated by a new research domain, the so-called privacy preserving data mining. Association rule hiding is a new technique in data mining, which studies the problem of hiding sensitive association rules from within the data.

Association Rule Hiding for Data Mining addresses the problem of “hiding” sensitive association rules, and introduces a number of heuristic solutions. Exact solutions of increased time complexity that have been proposed recently are presented, as well as a number of computationally efficient (parallel) approaches that alleviate time complexity problems, along with a thorough discussion regarding closely related problems (inverse frequent item set mining, data reconstruction approaches, etc.). Unsolved problems, future directions and specific examples are provided throughout this book to help the reader study, assimilate and appreciate the important aspects of this challenging problem.

Association Rule Hiding for Data Mining is designed for researchers, professors and advanced-level students in computer science studying privacy preserving data mining, association rule mining, and data mining. This book is also suitable for practitioners working in this industry.

Association Rule Hiding for Data Mining 2010th Table of contents:

Part I: Fundamental Concepts

1. Background
2. Classes of Association Rule Hiding Methodologies
3. Other Knowledge Hiding Methodologies
4. Summary

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Part II: Heuristic Approaches

5. Distortion Schemes
6. Blocking Schemes
7. Summary

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Part III: Border-Based Approaches

8. Border Revision for Knowledge Hiding
9. BBA Algorithm
10. Max-Min Algorithms
11. Summary

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Part IV: Exact Hiding Approaches

12. Menon’s Algorithm
13. Inline Algorithm
14. Two-Phase Iterative Algorithm
15. Hybrid Algorithm
16. Parallelization Framework for Exact Hiding
17. Quantifying the Privacy of Exact Hiding Algorithms
18. Summary

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Part V: Epilogue

19. Conclusions
20. Roadmap to Future Work

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