| Autor: |
kavitha d, Dr.,Adilakshmi T., Dr. Chandra Mohan M. |
| Rok vydání: |
2022 |
| Zdroj: |
International Journal of Engineering Research in Computer Science and Engineering. 9:38-40 |
| ISSN: |
2394-2320 |
| DOI: |
10.36647/ijercse/09.09.art011 |
| Popis: |
In this paper we propose a Privacy preserving mechanism of big data using GDTM along with Random Number generators. Given the rapid explosion of data being used across Enterprises, Individuals and Sensors, billions of data is being streamed and exchanged across the network. There is a high possibility of sensitive data being exchanged and stored, it's important to preserve sensitive data of Individuals and Enterprise data.Most of the current techniques of privacy preserving in particular in the areas of data perturbation has been done on Static data. Given the dynamic nature of the applications and the huge data that is being generated it's important to evaluate the privacy preserving on big data without losing the accuracy.Our research contribution is on Privacy preserving of big data using Geometric data transformation, random number generator and GNN techniques [5].We would like to extend our research further on improving the accuracy of big data. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
