Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2151
Title: Privacy preserving data mining: A review of the state of the art
Authors: Sharma S
Ahuja S.
Keywords: Association
Classification
Clustering
Data mining
Distortion
K-anonymity
Outsourcing
Privacy preserving.
Issue Date: 2019
Publisher: Springer Verlag
Abstract: Safeguarding of security in information mining has risen as an outright essential for trading secret data as far as information investigation, approval, and distributing. Constantly raising web phishing postured serious danger on across the board proliferation of delicate data over the web. Then again, the questionable sentiments and conflicts intervened unwillingness of different data suppliers towards the unwavering quality insurance of information from exposure frequently comes about absolute dismissal in information sharing or off base data sharing. This article gives an all-encompassing outline on new point of view and precise translation of a rundown distributed literary works through their fastidious association in subcategories. The crucial ideas of the current protection safeguarding information mining strategies, their benefits, and deficiencies are displayed. The present security protecting information mining methods are ordered in light of contortion, affiliation administer, shroud affiliation control, scientific categorization, bunching, cooperative characterization, outsourced information mining, disseminated, and k-anonymity, where their remarkable points of interest and hindrances are underlined. This watchful investigation uncovers the past improvement, show examine challenges, future patterns, the holes and weaknesses. Promote huge improvements for more powerful security insurance and safeguarding are confirmed to be compulsory.
URI: 10.1007/978-981-13-0761-4_1
http://hdl.handle.net/123456789/2151
Appears in Collections:Conferences

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