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Article type: Research Article
Authors: Huynh Trieu, Vya; * | Le Quoc, Haib | Truong Ngoc, Chauc
Affiliations: [a] Information Technology Faculty, Pham Van Dong University, Quang Ngai, Vietnam | [b] Information Technology Faculty, Quang Tri Teacher Training College, Quang Tri, Vietnam | [c] Information Technology Faculty, Da Nang University, Da Nang, Vietnam
Correspondence: [*] Corresponding author: Vy Huynh Trieu, Information Technology Faculty, Pham Van Dong University, Quang Ngai, Vietnam. E-mail: [email protected].
Abstract: Privacy-preserving utility itemset mining is the process of hiding sensitive-high utility itemsets (SHUIs) appearing in original database such that they will not be discovered in the sanitized database. The purpose of SHUI hiding algorithm is to conceal the set of SHUIs while minimizing the side effects which caused by data distortion process. In this paper, a novel algorithm, named EHSHUI (An Efficient Algorithm for Hiding Sensitive-high utility Itemsets), is proposed to minimize the side effects of the sanitization process. The proposed algorithm includes three heuristic steps: (1) The transaction on which the SHUI achieves maximal utility among transactions containing it is specified as victim transaction; (2) The item that causes minimal impacts on non-SHUIs is selected as victim item; and (3) An exactly number of utility is calculated for reducing internal utility of victim item from victim transaction. This strategy exactly identifies item and transaction for data modification such that it minimizes the impacts on non-SHUIs, data distortions, and the time to access database. The experiment results illustrate that the proposed algorithm achieves higher performance and lower side effects than the state-of-the-art.
Keywords: High utility mining, high utility itemset, sensitive-high utility itemset hiding, privacy-preserving utility mining
DOI: 10.3233/IDA-194697
Journal: Intelligent Data Analysis, vol. 24, no. 4, pp. 831-845, 2020
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