Volume 20 No 20 (2022)
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IMPROVING THE DIGITAL DATA PROTECTION BY EMBEDDING THE FEATURES OF DEEP LEARNING AND BLOCKCHAIN TECHNOLOGY IN STEGANOGRAPHIC PROCESS
Ms. Ayushi Chaudhary, Dr. Ashish Sharma
Abstract
With the advancement in technology, the amount of data produced has also been increased. So it is very difficult to maintain the huge quantity of data produced in the form of hard files. Keeping the data in the form of digital form helps in storing and maintaining large quantity of data. But securing data in any form is very challenging. Proper security techniques must be used to store and maintain the data. One of the approach to hide the information present in digital is called steganography. The digital forms of data considered for steganographic process are images, audios and videos. In the current methodology, encryption is used in the steganographic process to hide the information present in the images, audios and videos. The purpose of using encryption is to securely hide the information. But as we are moving forward in technological world, security using encryption is not sufficient. So the proposed method concentrates on improving the security techniques used in steganography by introducing the concept of blockchain technology. With the intention of automating the process of document classification into either image, video or audio; the features of deep learning have been embedded. Overall the proposed work aims to improve the data protection and appending the cognitive capacity into steganography framework. The proposed work is aiming to achieve the highest level of degree by adding the blockchain technology in addition to encryption, where encryption is treated as the first level of security and blockchain storage mechanism is treated as second level of security. Apart from security improvement, document identification is automated through the features of deep learning so that the system will work with less manual intervention.
Keywords
Digital, Encryption, Steganography, Blockchain Technology, Deep Learning, Data Protection, security.
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