Abstract
Cryptography is the art and science of protecting information form intruders of data by making the information unintelligible (encryption), as well as, to retrieve the original data (decryption). Good cryptography means that the information is encrypted in such a way that a brute force attack against the key or cryptography algorithm are all impossible. Up to date, several ciphers utilizing complex mathematics have been proposed. But none of them are entirely secure and their vulnerabilities have been exposed. Therefore, novel cryptography algorithms, capable of provide superior protection, are highly desirable. In proposed work, a method for generating a key from an alphanumeric login password is introduced and implementation of symmetric-key encryption and decryption using an autoencoder neural network. Our experiments show that proposed method overcome traditional cryptography algorithms, at lest when small text file are used, and it is extremely hard to crack.
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Quinga-Socasi, F., Zhinin-Vera, L., Chang, O. (2021). A Deep Learning Approach for Symmetric-Key Cryptography System. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Proceedings of the Future Technologies Conference (FTC) 2020, Volume 1. FTC 2020. Advances in Intelligent Systems and Computing, vol 1288. Springer, Cham. https://doi.org/10.1007/978-3-030-63128-4_41
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DOI: https://doi.org/10.1007/978-3-030-63128-4_41
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