About

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