Manuscript Number : CSEIT1953193
Secure Data Protection Using Slicing as a Confusion Technique
Authors(2) :-V Veda Sahithi, V Swarna Kamalam Data Mining deals with automatic extraction of previously unknown patterns from large amounts of data sets. These data sets typically contain sensitive individual information or critical business information, which consequently get exposed to the other parties during Data Mining activities. Secure data protection has been one of the greater concerns in data mining. Several anonymization techniques, such as generalization and bucketization, have been designed for privacy protective microdata publishing. The generalization loses considerable amount of information, especially for high dimensional data. Bucketization, on the other hand, does not prevent membership disclosure and does not apply for data that do not have a clear separation between quasi-identifying attributes and sensitive attributes. Solution to this problem is provided by we introduce a novel data anonymization technique called slicing to improve the current state of the art.
V Veda Sahithi Data Mining, Privacy Protection, Data anonymization, Security, L diversity. Publication Details Published in : Volume 5 | Issue 4 | July-August 2019 Article Preview
Information Technology Department, JNTUH University/Bhoj Reddy Engineering College for Women, Hyderabad, Telangana, India
V Swarna Kamalam
Information Technology Department, JNTUH University/Bhoj Reddy Engineering College for Women, Hyderabad, Telangana, India
Date of Publication : 2019-08-31
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 297-301
Manuscript Number : CSEIT1953193
Publisher : Technoscience Academy
Journal URL : https://res.ijsrcseit.com/CSEIT1953193
Citation Detection and Elimination |
| |
BibTeX | RIS | CSV