IJSRSET calls volunteers interested to contribute towards the scientific development in the field of Science, Engineering and Technology

Home > IJSRSET1623208                                                     

Privacy Preserving Updates for Anonymzation Data Using ℓ -Diversity


Suyog Vilas Patil, Prof. K. B. Manwade
  • Abstract
  • Authors
  • Keywords
  • References
  • Details
To prevent misuse of sensitive data by the unauthorized/application users and provide both privacy and security of the sensitive data. The privacy preservation mechanism is to protect the data from unauthorized user. Privacy Protection Mechanism (PPM) can satisfy privacy requirements such as k-anonymity and l-diversity. The privacy protection mechanism (PPM) is a general method used to transform the original data into some anonymous form to prevent from accessing owners sensitive information. PPM meets privacy requirement through k-anonymity it provides better privacy for the sensitive information which is to sbe shared. The privacy is achieved by the high accuracy of the user information. The ? -diversity method is an extension of the k-anonymity method, it is more efficient than the k-anonymity method. It avoids the attacks like background knowledge attack and others in k-anonymity method. In this paper we analyze ?-diversity method with different techniques.

Suyog Vilas Patil, Prof. K. B. Manwade

Privacy Protection Mechanism, k-anonymity, Access Control Mechanism, ?-diversity

  1. Zahid Pervaiz, Arif Ghafoor, Walid G. Aref, "Precision-Bounded Access Control Using Sliding-Window Query Views for Privacy-Preserving Data Streams", IEEE Trans. Knowl. Data Eng, July 2015.
  2. Z.Pervaiz,W.G.Aref, A.Ghafoor,andN. Prabhu, "Accuracy constrained privacy-preserving access control mechanism for relational data", IEEE Trans. Knowl. Data Eng., April 2014.
  3. T. Ghanem, A. Elmagarmid, P. Larson, and W. Aref, "Supporting views in data stream management systems," ACM Trans. Database Syst., 2010.
  4. J. Cao, B. Carminati, E. Ferrari, and K. Tan, "Castle: Continuously anonymizing data streams," IEEE Trans. Dependable Secure Comput. May/Jun. 2011.
  5. C. Clifton and T. Tassa, "On syntactic anonymity and differential privacy," in Proc. IEEE Int. Conf. Data Eng. Workshop Privacy-Preserving Data Publication Anal., 2013.
  6. B. Zhou, Y. Han, J. Pei, B. Jiang, Y. Tao, and Y. Jia, "Continuous privacy preserving publishing of data streams," in Proc. 12th Int. Conf. Extending Database Technol.: Adv. Database Technol., 2009.
  7. Sai Wu,Xiaoli Wang,Sheng Wang, Zhenjie Zhang,"k-Anonymity for crowd sourcing Database" IEEE Trans. Knowl. Data Eng, sept 2014.

Publication Details

Published in : Volume 2 | Issue 4 | July-August - 2016
Date of Publication Print ISSN Online ISSN
2016-08-30 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
69-72 IJSRSET1623208   Technoscience Academy

Cite This Article

Suyog Vilas Patil, Prof. K. B. Manwade, "Privacy Preserving Updates for Anonymzation Data Using ℓ -Diversity", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 4, pp.69-72, July-August-2016.
URL : http://ijsrset.com/IJSRSET1623208.php