CENG 642
Privacy Preserving Data Mining
Due to the combinatorial nature of the problem, the proposed methodologies span from simple, time and memory efficient heuristics and border-based approaches, to exact hiding algorithms that offer guarantees on the quality of the computed hiding solution at an increased, however, computational complexity cost.
| Topics |
| Introduction to Privacy Preserving Data Mining and Association Rule Hiding |
| Background (Terminology and Preliminaries) |
| Classes of Association Rule Hiding Methodologies |
| Other Knowledge Hiding Methodologies |
| Heuristic Approaches |
| Border Based Approaches |
| Max–Min Algorithms (BBA Algorithm) |
| Max–Min Algorithms (Other) |
| Exact Hiding Approaches (Menon’s Algorithm) |
| Exact Hiding Approaches (Inline Algorithm) |
| Exact Hiding Approaches (Two–Phase Iterative Algorithm) |
| Exact Hiding Approaches (Hybrid Algorithm) |
| Exact Hiding Approaches (Paralelization Framework) |
| Quantifying the Privacy of Exact Hiding Algorithms |
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