DNA-Genetic Encryption Technique

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In this paper , we propose the technique of DNA-Genetic Encryption (D-GET) to make the technique more reliable and less predictable. In this process, any form of digital data is binarized and transformed into DNA sequencing, reshaping, encrypting, crossover, mutating and then reshaping. D-GET ‘s main stages are repeated three times or more. Encrypted data is transmitted in a text or image file format. On the other hand, the receiver uses D-GET to decode and reshape the obtained data to the original data. This technique often converts the text into a picture and vice versa to improve security and numerous key sequences to increase the degree of diffusion and uncertainty, making it difficult to decode the resulting cypher data and making a perfect system of secrecy possible. Experimental findings show that the proposed technique has multilayer defence phases based on multi-stage and genetic operations against various attacks and a higher degree of security. Decrypted information is appropriate because of the total distinction between it and confidential information.


A modern cryptographical prototype is DNA cryptography. DNA is a nucleic acid which contains instructions for genetics. Adenine (A), cytosine ( C), guanine ( G) and thymine ( T) form the four bases present in DNA. Parallel processing capabilities are the greatest advantage of DNA cryptography. The approach to biomolecular cryptography based on DNA is planned. A new generation DNA-based key system is proposed to improve computation based on the DNA-based key expansion matrix using random key generation scheme speed. It proposes a novel and special technique based on biological simulation for DNA encryption and decryption. The plaintext is similarly split into two halves and translated for each session to DNA sequences using unique encoding table generation. After that, after applying suggested technique measures, the cypher text is produced. Some latest DNA Cryptography works are discussed and compared. Based on a secured symmetrical key generation , a new DNA cryptography algorithm is suggested. This encryption algorithm consists of encryption, random key generation and decryption in three steps. The text is translated to ASCII and then to DNA code at the encryption level. This initial cypher is translated to the final cypher by using random key-generated DNA sequences. The DNA-Genetic Encryption Technique (D-GET) is suggested in this paper. The hidden information was translated into binary data and then into DNA sequences in this technique. The D-GET is, moreover, an iterative algorithm. A round is called an iteration, and the number of iterations is three or more. There are four operations in-round and it’s iterative in nature. Iteration requires encryption, the method of reshaping and genetic operations. Furthermore, a symmetrical key is used. You may use any format of data type as secret data , i.e. text, word document, pixel image, audio , and video. Experimental studies indicate that reconstructed information is a standard copy of secret information. And they also show that the technique proposed maintains perfect security.


In order to boost information security, this paper proposes the DNA-Genetic Encryption Technique (D-GET), which is an iterative algorithm. You may encrypt any form of data ( i.e., message,) Pre-processing, symmetric key encryption, reshaping and crossover and mutation are the principal stages of the proposed technique. They are clarified as follows.

A. Pre-processing Stage

This information has to be prepared after reading secret data, depending on its type. The ASCII values are translated in the case of a text file. Group them into 8 bit binary data. Each of the two adjacent bits is transferred to the four bases; adenine (A), cytosine ( C), guanine ( G) and thymine ( T), located in the DNA. According, for example, to Table 1.

In the event of text data are read into 8-bit binary data. Each of the two adjacent bits is transferred to the four bases; adenine (A), cytosine ( C), guanine ( G) and thymine ( T), located in the DNA.

B. Encryption stage

Symmetric and asymmetric key algorithms are two categories of cryptographic algorithms. A common key is exchanged between the sender and the recipient in the Symmetric Scheme. Asymmetric schemes have mathematically connected keys that are public and private. High-speed cryptography technology is the key advantage of the symmetric cryptographic algorithm and is more suitable for encrypting large volumes of data. The symmetric key is then used in the proposed approach based on DNA-based cryptographic algorithm.

Encrypt using the key after converting binary data to DNA sequencing. A DNA sequence or binary string can be the answer. Variable duration of the key. If one or both of the DNA sequence key data and DNA sequence sequences are converted to binary form, then an exclusive OR operation is performed on the corresponding DNA sequence elements and converted back to the DNA sequence.

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C. Reshaping Stage

A simple genetic algorithm consists of three operators after encryption: replication, crossover and mutation. The reshaping process is used to generate genetic material that moves to the next activity and iteration in the form of the chromosome population. In this step, the first chromosome number and length are determined. For each round, these values can be constant and varied. Reshape it by aligning the DNA sequence into rows to create the chromosomes (chromosome population) of parents with pre-defined length.

D. Crossover Stage

The next procedure is crossover after constructing the chromosomes of the parents.

There are two crossover forms. These can be used sequentially in rounds of technique. In the first one, in the mating pool, parents are chosen. A single-point crossover point is then chosen between the first and last bits of the chromosomes of the parents, producing two new offspring by swapping parent 1 and parent 2 heads.

E. Mutation Stage

The chromosomes are subject to mutation following the crossover process. Mutation is the modification of elements of a string. It uses two forms of mutation. Convert data to binary vector in the first one and define two mutation points between the first and last bits, then complement bits between i.e. mutation of single point changes from 1 to 0, and vice versa. In the second form of mutation, transform each of the four bits to two bases of DNA (1010  CG), for example: according to

The probability frequency of crossover and mutation operation is 100%. Encrypt and reshape data to pass to next round. The number of rounds depends on a predefined number of iterations. Transmit the encrypted data in text/image format file. At the receiver side, binaries received data and convert it to DNA sequencing and reshape, decrypt, crossover, mutate, decrypt and reshape to original format. The sequence of stages D-GET is illustrated in figure 2 (b). Figure 2 (a) illustrates the scenario of the stages of D-GET.


The D-GET is implemented in the AMD Athlon(tm) II X2 220 Processor, 2.80GHz and 4 GB RAM on Windows 8.1 64-BIT operating system. We conduct experiments to test the efficacy of the proposed technique and run it with various types of secret data.

Using all manner of cryptanalytic, mathematical and brute-force attacks, cryptanalysts attack any encrypted data to discover its contents. A successful encryption technique against them should be robust. So, there are some features that need to be achieved. Here There is no relationship between, before encryption, sensitive data values and, after encryption, encrypted data values. Encryption should be blended around the various hidden data components so that nothing in its original position is presented.


D-GET is implemented in this article. The D-GET, based on multi-iteration and genetic activities, is a more stable encryption technique. Operations, encryption, rotation, crossover, mutation, and reshapes that improve the standard of encryption are also included. D-GET operations and modifications to the original data size and format. In addition, the negligible relationship in both the hidden data and its encrypted data decreases the possibilities of cryptanalysis and breaking the cypher. In addition, the technique has multilayer defence phases that achieve confidentiality and provide data with more security, productivity and robustness and protects against detection. We would standardise D-GET in future work and try to minimise transmission


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