• Title/Summary/Keyword: 민감 빈발 항목집합

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Border-based HSFI Algorithm for Hiding Sensitive Frequent Itemsets (민감한 빈발항목집합을 숨기기 위한 경계기반 HSFI 알고리즘)

  • Lee, Dan-Young;An, Hyoung-Keun;Koh, Jae-Jin
    • Journal of Korea Multimedia Society
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    • v.14 no.10
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    • pp.1323-1334
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    • 2011
  • This paper suggests the border based HSFI algorithm to hide sensitive frequent itemsets. Node formation of FP-Tree which is different from the previous one uses the border to minimize the impacts of nonsensitive frequent itemsets in hiding process, including the organization of sensitive and border information, and all transaction as well. As a result of applying HSFI algorithms, it is possible to be the example transaction database, by significantly reducing the lost items, it turns out that HSFI algorithm is more effective than the existing algorithm for maintaining the quality of more improved database.

An Extended Frequent Pattern Tree for Hiding Sensitive Frequent Itemsets (민감한 빈발 항목집합 숨기기 위한 확장 빈발 패턴 트리)

  • Lee, Dan-Young;An, Hyoung-Geun;Koh, Jae-Jin
    • The KIPS Transactions:PartD
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    • v.18D no.3
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    • pp.169-178
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    • 2011
  • Recently, data sharing between enterprises or organizations is required matter for task cooperation. In this process, when the enterprise opens its database to the affiliates, it can be occurred to problem leaked sensitive information. To resolve this problem it is needed to hide sensitive information from the database. Previous research hiding sensitive information applied different heuristic algorithms to maintain quality of the database. But there have been few studies analyzing the effects on the items modified during the hiding process and trying to minimize the hided items. This paper suggests eFP-Tree(Extended Frequent Pattern Tree) based FP-Tree(Frequent Pattern Tree) to hide sensitive frequent itemsets. Node formation of eFP-Tree uses border to minimize impacts of non sensitive frequent itemsets in hiding process, by organizing all transaction, sensitive and border information differently to before. As a result to apply eFP-Tree to the example transaction database, the lost items were less than 10%, proving it is more effective than the existing algorithm and maintain the quality of database to the optimal.