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Research Article 


A Novel Hybrid Approach of Suppression and Randomization for Privacy Preserving Data Mining

Vibhor Sharma, Dheresh Soni, Deepak Srivastava, Dr. Pramod Kumar.

Abstract
In the era of technology advancement, knowledge extraction from large amount of data is very much important task. The process of data mining is applied to get the useful information from the data stored in a centralized server for important decision making process of multiple organizations. When multiple organizations collect the data for mutual gain, it gets vulnerable to individualís private data. Different approaches such generalization, perturbation, cryptography and randomization are used for taking care of the confidentiality of any individualís private data. Each of these methods has their own pros and cons like in anonymization, huge loss of information can take place. Data that is used in the process of data mining contain many attributes which hold confidential data of an individual and many attributes can reveal the private information of an individual, if those are associated with each other. These attributes are called quasi identifiers (QID). Individually these attributes donít breach the security but in a combined way these may be vulnerable towards the security of private data. Thus, there is the requirement of an approach to overcome the problem of disclosing of private data through quasi identifiers. Our proposed method of combining the suppression and randomization presents the solution to this problem. The method conserves the data privacy with the zero information loss in the process of regaining the actual values. The proposed work is carried out by making a local centralized server and outcomes are matched up with anonymization process to obtain the better results.

Key words: s Prime- Anonymization, Computation time, Privacy preservation, Randomization, Suppression.


 
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How to Cite this Article
Pubmed Style

Vibhor Sharma, Dheresh Soni, Deepak Srivastava, Dr. Pramod Kumar. A Novel Hybrid Approach of Suppression and Randomization for Privacy Preserving Data Mining. EEO. 2021; 20(5): 2451-2457. doi:10.17051/ilkonline.2021.05.267


Web Style

Vibhor Sharma, Dheresh Soni, Deepak Srivastava, Dr. Pramod Kumar. A Novel Hybrid Approach of Suppression and Randomization for Privacy Preserving Data Mining. http://ilkogretim-online.org//?mno=62496 [Access: April 09, 2021]. doi:10.17051/ilkonline.2021.05.267


AMA (American Medical Association) Style

Vibhor Sharma, Dheresh Soni, Deepak Srivastava, Dr. Pramod Kumar. A Novel Hybrid Approach of Suppression and Randomization for Privacy Preserving Data Mining. EEO. 2021; 20(5): 2451-2457. doi:10.17051/ilkonline.2021.05.267



Vancouver/ICMJE Style

Vibhor Sharma, Dheresh Soni, Deepak Srivastava, Dr. Pramod Kumar. A Novel Hybrid Approach of Suppression and Randomization for Privacy Preserving Data Mining. EEO. (2021), [cited April 09, 2021]; 20(5): 2451-2457. doi:10.17051/ilkonline.2021.05.267



Harvard Style

Vibhor Sharma, Dheresh Soni, Deepak Srivastava, Dr. Pramod Kumar (2021) A Novel Hybrid Approach of Suppression and Randomization for Privacy Preserving Data Mining. EEO, 20 (5), 2451-2457. doi:10.17051/ilkonline.2021.05.267



Turabian Style

Vibhor Sharma, Dheresh Soni, Deepak Srivastava, Dr. Pramod Kumar. 2021. A Novel Hybrid Approach of Suppression and Randomization for Privacy Preserving Data Mining. Elementary Education Online, 20 (5), 2451-2457. doi:10.17051/ilkonline.2021.05.267



Chicago Style

Vibhor Sharma, Dheresh Soni, Deepak Srivastava, Dr. Pramod Kumar. "A Novel Hybrid Approach of Suppression and Randomization for Privacy Preserving Data Mining." Elementary Education Online 20 (2021), 2451-2457. doi:10.17051/ilkonline.2021.05.267



MLA (The Modern Language Association) Style

Vibhor Sharma, Dheresh Soni, Deepak Srivastava, Dr. Pramod Kumar. "A Novel Hybrid Approach of Suppression and Randomization for Privacy Preserving Data Mining." Elementary Education Online 20.5 (2021), 2451-2457. Print. doi:10.17051/ilkonline.2021.05.267



APA (American Psychological Association) Style

Vibhor Sharma, Dheresh Soni, Deepak Srivastava, Dr. Pramod Kumar (2021) A Novel Hybrid Approach of Suppression and Randomization for Privacy Preserving Data Mining. Elementary Education Online, 20 (5), 2451-2457. doi:10.17051/ilkonline.2021.05.267








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