Pertinent Exploration of Privacy Preserving Perturbation Methods
Vijaya Pinjarkar1, Amit Jain2, Anand Bhaskar3, Prateek Srivastava4
1Vijaya Pinjarkar, Ph.D. Scholar, department of Computer Science and Engineering, Sir Padampat Singhania University, Udaipur, Rajasthan, Assistant Professor K.J. Somaiya Institute of Engineering & Information Technology, Mumbai, India.
2Amit Jain, Assistant Professor, Computer Science and Engineering, Sir Padampat Singhania University, Udaipur, Rajasthan, India.
3Anand Bhaskar, Head & Assistant Professor, Electronics & Communication Engineering, Sir Padampat Singhania University, Udaipur, Rajasthan, India.
4Prateek Srivastava, Assistant Professor, Computer Science and Engineering, Sir Padampat Singhania University, Udaipur, Rajasthan, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 20, 2020. | Manuscript published on March 30, 2020. | PP: 1945-1949 | Volume-8 Issue-6, March 2020. | Retrieval Number: F8007038620/2020©BEIESP | DOI: 10.35940/ijrte.F8007.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Digital era generates a huge amount of data in many sectors like education, medical, banking, business, marketing, etc. which can be used for research motive, analysis, prediction of trends, statistics, etc. Data mining techniques are useful in finding patterns, trends, and knowledge from such huge data. The data holders are not ready to share data because there are chances of privacy leakage. Sharing of such data immensely helps researchers to obtain knowledge from it, especially medical data. Privacy preserving data mining is one way where researchers will get mine data for gaining knowledge without breaching the privacy. In the medical sector there is a branch called the mental health section, where high confidentiality of data is maintained and is needed. Owners are not ready to share data for research motives. Mental health is nowadays a topic that is most frequently discussed when it comes to research. PPDM allows sharing data with the researcher, where the privacy of data is maintained by using perturbation techniques giving relief to doctors (owner of data). The current paper experiments and analyses different perturbation methods to preserve privacy in data mining.
Keywords: Mental Health, Perturbation, Privacy Preserving Data Mining
Scope of the Article: Data Mining.