Maintening multi-level confidentiality on big data using Pk-anonymization methods and cryptographic techniques

Ahmed Mohammed, G. Babu
2018 Advances in Modelling and Analysis B  
Anonymization innovation is basic for accomplishing assurance on security when utilizing individual data. In the time of bigdata a lot of data has been aggregated by different data repositories. Manu problems are arised in personal informations are recognized by coordinating through other information. Anonymization process in bigdata being a test to change over individual information into non individual information. With the assistance of the guide reduction structure the huge number of
more » ... tions and associations use anonymization methods to process massive volume informational collections. Security safeguarding and elevated function of Data is conceivable because of the guide diminishing structure and k-Anonymization expertise which can be effectively used with big data.In this manuscript, probabilistic k-anonymization process is used for the information conversion. Here we give multilevel security to our information to make framework more secure by using Pk-anonymization.by using this technique the personal data of a individual is converted into a un-identified format which is highly secured. One of the primary destinations of these framework is to prevent from straight variety assault and other non-straight assaults. To give multilevel security we consolidate cryptography and steganography approaches also along with Pk-Anonymization method. The advantage of these plan is that steganography can work on encoded content and thus it offers a twofold layer information assurance and heartiness for secure information transmission over an open channel. The cryptographic mechanisms are applied on the data which is modified using Pk-Anonymization technique and secure information transferring can be achieved over the cloud.
doi:10.18280/ama_b.610103 fatcat:qwrpdw5dqrayno7ikjffcsmny4