A Survey on Big Data Privacy Protection
Published: 2019
Author(s) Name: Sanjay Tiwari, Kumar Swastik and Sunita |
Author(s) Affiliation: Dept. of Comp. Science Engineering, Arya Institute of Engg. Tech. and Mgt., Jaipur, Rajasthan
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Abstract
As time is going by, the problem of phishing of data propagating through the internet has been threatening the privacy of users’ data. Data providers have a huge responsibility of protecting the privacy of personal data. Now the problem arises that while working and manipulating a huge amount of data (big data), how the privacy of confidential data is maintained. This can be only done by preserving security while we are mining the data or abstracting the data from a huge amount. This lead to a new research branch, which is Privacy Preserving Data Mining (PPDM), which is reviewed in this paper. This branch leads to develop good mining techniques so that the data is preserved while the data is being extracted for manipulation purposes. This paper discussing different PPDM techniques and their classification for data modification. Along with we will be going through various advantages and disadvantages of PPDM. This review is based on previous research which is helpful for new researches.
Keywords: Anonymization technique, Big data, Data mining, Data modification, Data phishing, Preservation, Privacy.
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