An analysis of privacy preservation techniques in data mining

Abhishek Sachan; Devshri Roy; P. V. Arun

doi:10.1007/978-3-642-31600-5_12

An analysis of privacy preservation techniques in data mining

Abhishek Sachan
, Devshri Roy
, P. V. Arun

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

16 Scopus citations

Abstract

Data mining techniques are used extensively for deducting the implicit, previously unknown, and potentially useful information from large data sets by using statistical and intelligent methodologies. The deduction of patterns or conclusions may uncover the information that may sometimes compromise the confidentiality and privacy obligations. Preservation of privacy is an important aspect of data mining and thus study of achieving some data mining goals without sacrificing the privacy of the individuals is not only demanding but also a task of practical importance. The analysis of privacy preserving data mining (PPDM) algorithms should consider the effects of these algorithms in mining the results as well as in preserving privacy. The privacy should be preserved in all the three aspects of mining as association rules, classifiers and clusters. In this paper we present a review of the commonly existing efficient methodologies in the context of privacy preservation in data mining.

Original language	English
Title of host publication	Advances in Computing and Information Technology- Proceedings of the 2nd International Conference on Advances in Computing and Information Technology, ACITY 2012- Volume 3
Editors	Natarajan Meghanathan, Nabendu Chaki, Dhinaharan Nagamalai
Publisher	Springer Verlag
Pages	119-128
Number of pages	10
ISBN (Print)	9783642315992
DOIs	https://doi.org/10.1007/978-3-642-31600-5_12
State	Published - 1 Jan 2013
Externally published	Yes
Event	2nd International Conference on Advances in Computing and Information Technology, ACITY 2012 - Chennai, India Duration: 13 Jul 2012 → 15 Jul 2012

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	178
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	2nd International Conference on Advances in Computing and Information Technology, ACITY 2012
Country/Territory	India
City	Chennai
Period	13/07/12 → 15/07/12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

Keywords

Counter terrorism
Cryptography
Data mining
Encrypted data
Privacy preserving

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-3-642-31600-5_12

Cite this

Sachan, A., Roy, D., & Arun, P. V. (2013). An analysis of privacy preservation techniques in data mining. In N. Meghanathan, N. Chaki, & D. Nagamalai (Eds.), Advances in Computing and Information Technology- Proceedings of the 2nd International Conference on Advances in Computing and Information Technology, ACITY 2012- Volume 3 (pp. 119-128). (Advances in Intelligent Systems and Computing; Vol. 178). Springer Verlag. https://doi.org/10.1007/978-3-642-31600-5_12

Sachan, Abhishek ; Roy, Devshri ; Arun, P. V. / An analysis of privacy preservation techniques in data mining. Advances in Computing and Information Technology- Proceedings of the 2nd International Conference on Advances in Computing and Information Technology, ACITY 2012- Volume 3. editor / Natarajan Meghanathan ; Nabendu Chaki ; Dhinaharan Nagamalai. Springer Verlag, 2013. pp. 119-128 (Advances in Intelligent Systems and Computing).

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title = "An analysis of privacy preservation techniques in data mining",

abstract = "Data mining techniques are used extensively for deducting the implicit, previously unknown, and potentially useful information from large data sets by using statistical and intelligent methodologies. The deduction of patterns or conclusions may uncover the information that may sometimes compromise the confidentiality and privacy obligations. Preservation of privacy is an important aspect of data mining and thus study of achieving some data mining goals without sacrificing the privacy of the individuals is not only demanding but also a task of practical importance. The analysis of privacy preserving data mining (PPDM) algorithms should consider the effects of these algorithms in mining the results as well as in preserving privacy. The privacy should be preserved in all the three aspects of mining as association rules, classifiers and clusters. In this paper we present a review of the commonly existing efficient methodologies in the context of privacy preservation in data mining.",

keywords = "Counter terrorism, Cryptography, Data mining, Encrypted data, Privacy preserving",

author = "Abhishek Sachan and Devshri Roy and Arun, \{P. V.\}",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2013.; 2nd International Conference on Advances in Computing and Information Technology, ACITY 2012 ; Conference date: 13-07-2012 Through 15-07-2012",

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Sachan, A, Roy, D & Arun, PV 2013, An analysis of privacy preservation techniques in data mining. in N Meghanathan, N Chaki & D Nagamalai (eds), Advances in Computing and Information Technology- Proceedings of the 2nd International Conference on Advances in Computing and Information Technology, ACITY 2012- Volume 3. Advances in Intelligent Systems and Computing, vol. 178, Springer Verlag, pp. 119-128, 2nd International Conference on Advances in Computing and Information Technology, ACITY 2012, Chennai, India, 13/07/12. https://doi.org/10.1007/978-3-642-31600-5_12

An analysis of privacy preservation techniques in data mining. / Sachan, Abhishek; Roy, Devshri; Arun, P. V.
Advances in Computing and Information Technology- Proceedings of the 2nd International Conference on Advances in Computing and Information Technology, ACITY 2012- Volume 3. ed. / Natarajan Meghanathan; Nabendu Chaki; Dhinaharan Nagamalai. Springer Verlag, 2013. p. 119-128 (Advances in Intelligent Systems and Computing; Vol. 178).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Sachan, Abhishek

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PY - 2013/1/1

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AB - Data mining techniques are used extensively for deducting the implicit, previously unknown, and potentially useful information from large data sets by using statistical and intelligent methodologies. The deduction of patterns or conclusions may uncover the information that may sometimes compromise the confidentiality and privacy obligations. Preservation of privacy is an important aspect of data mining and thus study of achieving some data mining goals without sacrificing the privacy of the individuals is not only demanding but also a task of practical importance. The analysis of privacy preserving data mining (PPDM) algorithms should consider the effects of these algorithms in mining the results as well as in preserving privacy. The privacy should be preserved in all the three aspects of mining as association rules, classifiers and clusters. In this paper we present a review of the commonly existing efficient methodologies in the context of privacy preservation in data mining.

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Sachan A, Roy D, Arun PV. An analysis of privacy preservation techniques in data mining. In Meghanathan N, Chaki N, Nagamalai D, editors, Advances in Computing and Information Technology- Proceedings of the 2nd International Conference on Advances in Computing and Information Technology, ACITY 2012- Volume 3. Springer Verlag. 2013. p. 119-128. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-642-31600-5_12

An analysis of privacy preservation techniques in data mining

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this