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Privacy preserving data mining based on geometrical data transformation method (GDTM) and k-means clustering algorithm

In current era of sharing unlimited digital information via the network, protecting the privacy of information is crucial even during the data mining process due to a high possibility of the information security risks such as being abused or leakage. Such problems motivate the research in Privacy Pr...

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Main Authors: Sirat @ Md. Siraj, Maheyzah, Ithnin, Norafida, Kutty Mammi, Hazinah, Mat Din, Mazura, Jamadi, Nur Athirah
Format: Article
Published: International Journal of Innovative Computing (IJIC) 2018
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/82160/
https://doi.org/10.11113/ijic.v8n2.174
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spelling my.utm.821602019-11-06T03:51:14Z http://eprints.utm.my/id/eprint/82160/ Privacy preserving data mining based on geometrical data transformation method (GDTM) and k-means clustering algorithm Sirat @ Md. Siraj, Maheyzah Ithnin, Norafida Kutty Mammi, Hazinah Mat Din, Mazura Jamadi, Nur Athirah QA75 Electronic computers. Computer science In current era of sharing unlimited digital information via the network, protecting the privacy of information is crucial even during the data mining process due to a high possibility of the information security risks such as being abused or leakage. Such problems motivate the research in Privacy Preserving Data Mining (PPDM) and it became one of the newest trends. Therefore, this papers reviews the related works in terms of issues, approaches, techniques, performance quantification as well as thorough discussions on pros and cons of previous researches. We also propose an improved PPDM that applying Geometrical Data Transformation Method (GDTM) and K-Means Clustering Algorithm for optimum accuracy of mining and zero data loss while preserving the privacy of information. International Journal of Innovative Computing (IJIC) 2018 Article PeerReviewed Sirat @ Md. Siraj, Maheyzah and Ithnin, Norafida and Kutty Mammi, Hazinah and Mat Din, Mazura and Jamadi, Nur Athirah (2018) Privacy preserving data mining based on geometrical data transformation method (GDTM) and k-means clustering algorithm. International Journal of Innovative Computing (IJIC), 8 (2). pp. 1-7. ISSN 2180-4370 https://doi.org/10.11113/ijic.v8n2.174 DOI: 10.11113/ijic.v8n2.174
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Sirat @ Md. Siraj, Maheyzah
Ithnin, Norafida
Kutty Mammi, Hazinah
Mat Din, Mazura
Jamadi, Nur Athirah
Privacy preserving data mining based on geometrical data transformation method (GDTM) and k-means clustering algorithm
description In current era of sharing unlimited digital information via the network, protecting the privacy of information is crucial even during the data mining process due to a high possibility of the information security risks such as being abused or leakage. Such problems motivate the research in Privacy Preserving Data Mining (PPDM) and it became one of the newest trends. Therefore, this papers reviews the related works in terms of issues, approaches, techniques, performance quantification as well as thorough discussions on pros and cons of previous researches. We also propose an improved PPDM that applying Geometrical Data Transformation Method (GDTM) and K-Means Clustering Algorithm for optimum accuracy of mining and zero data loss while preserving the privacy of information.
format Article
author Sirat @ Md. Siraj, Maheyzah
Ithnin, Norafida
Kutty Mammi, Hazinah
Mat Din, Mazura
Jamadi, Nur Athirah
author_facet Sirat @ Md. Siraj, Maheyzah
Ithnin, Norafida
Kutty Mammi, Hazinah
Mat Din, Mazura
Jamadi, Nur Athirah
author_sort Sirat @ Md. Siraj, Maheyzah
title Privacy preserving data mining based on geometrical data transformation method (GDTM) and k-means clustering algorithm
title_short Privacy preserving data mining based on geometrical data transformation method (GDTM) and k-means clustering algorithm
title_full Privacy preserving data mining based on geometrical data transformation method (GDTM) and k-means clustering algorithm
title_fullStr Privacy preserving data mining based on geometrical data transformation method (GDTM) and k-means clustering algorithm
title_full_unstemmed Privacy preserving data mining based on geometrical data transformation method (GDTM) and k-means clustering algorithm
title_sort privacy preserving data mining based on geometrical data transformation method (gdtm) and k-means clustering algorithm
publisher International Journal of Innovative Computing (IJIC)
publishDate 2018
url http://eprints.utm.my/id/eprint/82160/
https://doi.org/10.11113/ijic.v8n2.174
_version_ 1654960001281687552
score 13.212979

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