Abstract The research of sensitive pattern hiding is important in privacy preserving data mining. Existing sensitive pattern hiding algorithms are originally designed for static database which cannot handle incremental datasets effectively and efficiently. To hide sensitive patterns in the incremental environment, a selection strategy for optimal victim items with minimal edge effect is designed based on sensitive pattern graph and a privacy preservation algorithm in the incremental updating database is proposed. The instance analysis and experimental results validate the correctness, efficiency and scalability of the proposed method.
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