LIQUID STEGANOGRAPHY-SECRET MESSAGE AS LIVING CELLS USING DNA COMPUTING
Author(s):
Vanathi P, Rashmika NRS, Poorani S, Vaishnavi R, Vedha A
Keywords:
Substitution technique, Recovery Algorithm, Playfair cipher technique.
Abstract
Over the decades, DNA-primarily based totally steganography has emerged as a promising area for securing touchy statistics transmitted over an untrusted channel. Cryptography and Steganography are two methods used for secure information transmission. The process of data hiding involves using a carrier to conceal data such as images, video, and audio. Leaks of secret messages (SM) can have disastrous consequences, which has led to the development of numerous technologies for safeguarding SM. Steganography has been used for centuries and aims to keep SMs hidden. Throughout history, various types of steganography have existed, such as steganography ink, acrostic, wax-covered boards, and even messages written in hair by ancient Greeks. With the introduction of image, audio, and video technologies, steganography has evolved, and researchers have recently turned to using DNA to transmit and protect SMs. This project proposes Liquid Steganography, a scheme that uses a DNA-based steganography technique called data hiding using double DNA sequences to hide SMs in living cells. The cell can be stored and transmitted in liquid, paper, or plate form, disguising it as a drink, cosmetics, or another item. The key table and key pool are distributed in advance to both the sender and receiver in Liquid Steganography. The proposed system comprises two algorithms: substitution and recovery. The Substitution algorithm goes through several steps to encrypt and hide messages within a DNA sequence, while the Recovery Algorithm is used to retrieve the original secret message from the DNA sequence. This project is a preliminary investigation into a new model for hiding messages in living cells, and with DNA steganography being a new field, there are many opportunities for improving existing steganography and steganalysis approaches.
Article Details
Unique Paper ID: 159095

Publication Volume & Issue: Volume 9, Issue 11

Page(s): 414 - 422
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