The need to a robust and effective methods for secure data transferring makes the more credible. Two disciplines for data encryption presented in this paper: machine learning and deoxyribonucleic acid (DNA) to achieve the above goal and following common goals: prevent unauthorized access and eavesdropper. They used as powerful tool in cryptography. This paper grounded first on a two modified Hebbian neural network (MHNN) as a machine learning tool for message encryption in an unsupervised method. These two modified Hebbian neural nets classified as a: learning neural net (LNN) for generating optimal key ciphering and ciphering neural net CNN) for coding the plaintext using the LNN keys. The second granulation using DNA nucleated to increase data confusion and compression. Exploiting the DNA computing operations to upgrade data transmission security over the open nets. The results approved that the method is effective in protect the transferring data in a secure manner in less time
The huge improvement in the field of data innovation and the web presentation to a surge of infringement to go around and take data, the earnest requirement for the development of information assurance advancements and information encryption procedures. A new Programmatic OTP Algorithm using an unsystematic key generation for ciphering plaintext presented in this paper. This method, based on create randomly a number (n) called add number, where the plaintext characters converted to a binary form and splits into equal parts according to n value with 2n ciphering keys generated. The keys will be distributed on these parts to get ciphered text. Accordingly, one of these keys its generation number will be set for all different n’s. The different n’s occurred Consecutively to the number of characters consist the plain message unlike the traditional OTP algorithm. This method characterized by a facility that the same generated key can produce different ciphering text using 2n probability. The proposed methodology has been proved as perfect ciphering method compared with OTP using statistical tests
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