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DNA-Based Steganography Using Neural Networks

Authors: Marghny H. Mohammed; Ahmed I. Taloba; Botheina H. Ali;

DNA-Based Steganography Using Neural Networks

Abstract

Steganography is the art or the science of hiding information such as text, audio, video, etc. in another cover media such as text, audio, video and recently the information is hidden in deoxyribonucleic acid (DNA) sequences which have been become a cover medium for steganography. In this paper, a high secured, a high capacity, preserved algorithm is proposed for hiding data in DNA without affecting its functionality or its type. The proposed algorithm is developed using a Neural Network algorithm and the least significant bit (LSB) of the DNA codon to give a lowest cracking probability and a lower execution time. The secret messages are hidden inside the reference DNA sequence and the performance is measured by calculating the cracking probability, capacity, payload and bpn.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average
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