Research Area: CyberSecurity
The main purpose of Cryptography is to apply complex mathematics and logic to develop encryption and decryption processes,whereby the information is made unintelligible, and the original data is recovered, respectively.Thus avoiding unauthorized access to information. Up to date, various cryptography algorithms have been developed. Such as AES, 3DES, and RSA, where each cipher entails the advantages and drawbacks thereof.
On the one hand, traditional cryptography ciphers apply exhaustive serial operations using complex formulas and huge prime numbers, making encryption and decryption computing consuming and somehow vulnerable. On the other hand, recently machine learning and artificial intelligence have achieved significant improvements in Cryptography.
This work proposes an alternative deep learning encryption system with two principal components: (1) A particular type of neural network called auto encoder for encryption and de-encryption of data, (2) A key generation algorithm which transforms an alphanumeric password into a sequence of integer numbers used during the random processes of the training phase. Experimental results show that the proposed system overcome AES, DES, 3DES, and RSA when encrypting files of size no longer than 868KB. We also show that the proposed system may represent a meaningful contribution to the field of data security.
Name of the Researcher: Quinga Socasi Francisco
Name of the Supervisor(s): Chang Tortolero Oscar
Year of Completion: 2020
University: Yachay University
Thesis Link: Home Page Url
