Hiding informative association rule sets

Wang, Shyue-Liang; Parikh, Bhavesh; Jafari, Alireza

doi:10.1016/j.eswa.2006.05.022

Cited by 59 publications

(61 citation statements)

References 17 publications

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“…Algorithm used for Knowledge Hiding is ISL algorithm or DSR algorithm [2]. The main disadvantage of a blocking algorithm is the fact that the dataset, apart from the blocked values, is not distorted.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Minimization of Side Effects of Knowledge Hiding Based On Association Rule Mining

Waghchaure¹,

Khapale²,

Thulasi³

2014

IOSRJCE

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Section: Related Workmentioning

confidence: 99%

“…The one that is covered in the paper is just one kind of them, called support-based and confidence-based blocking schemes. Algorithm used For Knowledge Hiding is ISL algorithm or DSR algorithm [2]. The main disadvantage of a block in algorithm is the fact that the dataset, apart from the blocked values, is not distorted.…”

Section: Introductionmentioning

confidence: 99%

Minimization of Side Effects of Knowledge Hiding Based On Association Rule Mining

Waghchaure¹,

Khapale²,

Thulasi³

2014

IOSRJCE

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“…This approach involves efficient, fast and scalable algorithms that selectively sanitize a set of transactions from the original database to hide the sensitive association rules [5].It is divided further in to two types that are Distortion techniques and blocking technique. [5].…”

Section: Heuristic Based Approachmentioning

confidence: 99%

“…[5]. In [7] Algorithm DCIS (Decrease Confidence by Increase Support) and DCDS (Decrease Confidence by Decrease Support) are proposed.…”

Section: Heuristic Based Approachmentioning

confidence: 99%

Association Rule Hiding based on Heuristic Approach by Deleting Item at R. H. S. Side of Sensitive Rule

Kalariya¹,

Shah²,

Vala³

2015

IJCA

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Privacy preservation data mining is novel research area where data mining algorithms are analyzed for their side-effects they done on data privacy. Privacy preservation data mining (PPDM) deals with the problem of hiding the sensitive information while analyzing data. Many techniques are available for PPDM like data distortion, data hiding, rule hiding, data modification etc. Association rule hiding is one of the technique of PPDM. It hides sensitive rules which are generated by association rule generation algorithm before releasing database. This paper discusses different approaches of association rule hiding technique. In this paper, we propose a heuristic algorithm which provides privacy for sensitive rules while ensuring data quality. Proposed algorithm hides as many as possible rules at a time by modifying fewer transactions.

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“…In [39], two algorithms are proposed to hide information rule sets but side effects can be reduced by selecting the candidate transaction as the one having least number of frequent itemsets belong to it as well as performance can be enhanced by using Transaction ID List of items. In this paper, two algorithms are presented which are the enhancement of work done in [39,37] to improve the performance as well as to reduce the side-effect.…”

Section: Informative Association Rule Setsmentioning

confidence: 99%