A Robust Privacy Preservation by Combination of Additive and Multiplicative Data Perturbation for Privacy Preserving Data Mining
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چکیده
منابع مشابه
A Survey of Multiplicative Perturbation for Privacy-Preserving Data Mining
The major challenge of data perturbation is to achieve the desired balance between the level of privacy guarantee and the level of data utility. Data privacy and data utility are commonly considered as a pair of conflicting requirements in privacy-preserving data mining systems and applications. Multiplicative perturbation algorithms aim at improving data privacy while maintaining the desired l...
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Title of Thesis: On Random Additive Perturbation for Privacy Preserving Data Mining Author: Souptik Datta, Master of Science, 2004 Thesis directed by: Dr. Hillol Kargupta, Associate Professor Department of Computer Science and Electrical Engineering Privacy is becoming an increasingly important issue in many data mining applications. This has triggered the development of many privacy-preserving...
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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...
متن کاملPrivacy Preserving Data Mining
Through data mining collect large amount of data in many organizations. A key value of huge databases today is technical or financial research. In a huge collection of data there arises a key issue that is privacy. Due to personal interests, medical databases or business interests privacy is needed. Due to privacy infringement while performing the data mining operations this is often not possib...
متن کاملPrivacy Preserving Data Mining
There is a tremendous increase in the research of data mining. Data mining is the process of extraction of data from large database. Knowledge Discovery in database (KDD) is another name of data mining. Privacy protection has become a necessary requirement in many data mining applications due to emerging privacy legislation and regulations. One of the most important topics in research community...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2015
ISSN: 0975-8887
DOI: 10.5120/21192-3850