Call for Papers 2022

Oct 2023 - Volume 14, Issue 5
Deadline: 15 Sep 2023
Publication: 20 Oct 2023

Dec 2023 - Volume 14, Issue 6
Deadline: 15 Nov 2023
Publication: 20 Dec 2023




Title : A Technique to improve Security of Data in Multilevel Trust
Authors : A. Viji Amutha Mary, Dr. T. Jebarajan
Keywords : multilevel trust; perturbation; privacy preserving; data mining
Issue Date : Apr-May 2014
Abstract :
The Privacy Preserving Data Mining technique that is used widely to conserve security of data is a random perturbation method. The original data is modified and many copies are created according to the trust levels in each field. The addition of noise level also varies with each trust level. The amount of noise added to the lower order trust level is less, whereas it is high in the higher order trust level. There is a chance for the hackers to reconstruct the original data with some non linear techniques. This challenge is addressed by the proposal of a novel non linear technique. Here, the noise level of each copy is checked after perturbation of the actual data. If any similarity is found in the noise level, reconstruction of the original data is possible. Therefore, additional noise is included in the perturbed data. This process is repeated till zero percent of similarity of data is attained.
Page(s) : 67-70
ISSN : 0976-5166
Source : Vol. 5, No.2