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Abstract
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Article Information:
Privacy Preserving Data Mining
A.T. Ravi and S. Chitra
Corresponding Author: A.T. Ravi
Submitted: October 10, 2014
Accepted: November 3, 2014
Published: March 15, 2015 |
Abstract:
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Recent interest in data collection and monitoring using data mining for security and business-related applications has raised privacy. Privacy Preserving Data Mining (PPDM) techniques require data modification to disinfect them from sensitive information or to anonymize them at an uncertainty level. This study uses PPDM with adult dataset to investigate effects of K-anonymization for evaluation metrics. This study uses Artificial Bee Colony (ABC) algorithm for feature generalization and suppression where features are removed without affecting classification accuracy. Also k-anonymity is accomplished by original dataset generalization.
Key words: Adult dataset, Artificial Bee Colony (ABC) algorithm, data mining, K-anonymization, Privacy Preserving Data Mining (PPDM), ,
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Cite this Reference:
A.T. Ravi and S. Chitra, . Privacy Preserving Data Mining. Research Journal of Applied Sciences, Engineering and Technology, (8): 616-621.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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