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DOI: 10.14569/IJACSA.2019.0101239
PDF

Clustering based Privacy Preserving of Big Data using Fuzzification and Anonymization Operation

Author 1: Saira Khan
Author 2: Khalid Iqbal
Author 3: Safi Faizullah
Author 4: Muhammad Fahad
Author 5: Jawad Ali
Author 6: Waqas Ahmed

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 12, 2019.

  • Abstract and Keywords
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Abstract: Big Data is used by data miner for analysis purpose which may contain sensitive information. During the procedures it raises certain privacy challenges for researchers. The existing privacy preserving methods use different algorithms that results into limitation of data reconstruction while securing the sensitive data. This paper presents a clustering based privacy preservation probabilistic model of big data to secure sensitive information..model to attain minimum perturbation and maximum privacy. In our model, sensitive information is secured after identifying the sensitive data from data clusters to modify or generalize it.The resulting dataset is analysed to calculate the accuracy level of our model in terms of hidden data, lossed data as result of reconstruction. Extensive experiements are carried out in order to demonstrate the results of our proposed model. Clustering based Privacy preservation of individual data in big data with minimum perturbation and successful reconstruction highlights the significance of our model in addition to the use of standard performance evaluation measures.

Keywords: Big data; clustering; privacy preservation; reconstruction; perturbation

Saira Khan, Khalid Iqbal, Safi Faizullah, Muhammad Fahad, Jawad Ali and Waqas Ahmed, “Clustering based Privacy Preserving of Big Data using Fuzzification and Anonymization Operation” International Journal of Advanced Computer Science and Applications(IJACSA), 10(12), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101239

@article{Khan2019,
title = {Clustering based Privacy Preserving of Big Data using Fuzzification and Anonymization Operation},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101239},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101239},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {12},
author = {Saira Khan and Khalid Iqbal and Safi Faizullah and Muhammad Fahad and Jawad Ali and Waqas Ahmed}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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