Earticle

초록

영어

Privacy preserving data mining (PPDM) has become a popular research direction in data mining. Privacy preserving data mining is an approach to develop algorithms by which we can modify the utility values of original data using some techniques in order to protect sensitive information from unauthorized user. Protecting data against illegal access becomes a serious issue when this data is required to be shared onto the network due to some reasons. To hide the sensitive information, many approaches have been proposed. In this study, we are proposing an efficient method, for protecting high utility itemsets using distortion technique where the values for high utility items are altered to achieve the privacy. Algorithm is designed in such a way so as to handle privacy without disclosure of sensitive information. The algorithm can completely hide any given utility items by scanning data iteratively. The results when compared with existing one show significant reduction in execution time.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Proposed Algorithm
 4. Results and Discussion
 5. Conclusion and Future Work
 References

키워드

저자

• Anshu Chaturvedi [ Madhav Institute of Technology and Science, Gwalior – 474005, India, Jiwaji University, Gwalior – 474011, India, Jiwaji University, Gwalior – 474011, India ]
• D. N. Goswami [ Madhav Institute of Technology and Science, Gwalior – 474005, India, Jiwaji University, Gwalior – 474011, India, Jiwaji University, Gwalior – 474011, India ]
• Rishi Soni [ Madhav Institute of Technology and Science, Gwalior – 474005, India, Jiwaji University, Gwalior – 474011, India, Jiwaji University, Gwalior – 474011, India ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605