A new data security algorithm for the cloud computing based on genetics techniques and logical-mathematical functions

Abstract

With the rapid development of distributed system technologies, one of the biggest challenges facing the digital world is ensuring the security of sensitive and confidential data during transport and storage, which are considered the most critical challenges facing cloud computing. There are many techniques to enhance data security on cloud computing storage environment. Encryption is the most significant method for data protection. Therefore, many available encryption algorithms are used to provide security, integrity, and authorized access using many methods such as DNA. However, they still have some limitations. In this paper, a novel variant of cryptography techniques is designed to improve cloud computing security by using two layers of encryption. The first layer is inspired by Shannon’s theory of diffusion and confusion by the involvement of logical operations, such as (XOR, XNOR, shifting) with split the original plaintext and key into equal parts. The second layer is inspired from structures of genetics based on the Central Dogma of Molecular Biology for cryptographic purpose through simulation of the natural processes of genetic cryptography (translation from binary to DNA bases), transcription (regeneration from DNA to mRNA), and translation (regeneration from mRNA to protein). The experimental results enhanced data security that can be used to secure applications on cloud computing. The proposed algorithm’s experimental results presented a strong security level, an apparent enhancement of cipher size and execution time compared to existing techniques widely used in cloud computing.