Paper 2023/1292 Original: eprint.iacr.org/2023/1292 ↗

Enhancing Data Security: A Study of Grain Cipher Encryption using Deep Learning Techniques

Abstract

Data security has become a paramount concern in the age of data driven applications, necessitating the deployment of robust encryption techniques. This paper presents an in-depth investigation into the strength and randomness of the keystream generated by the Grain cipher, a widely employed stream cipher in secure communication systems. To achieve this objective, we propose the construction of sophisticated deep learning models for keystream prediction and evaluation. The implications of this research extend to the augmentation of our comprehension of the encryption robustness offered by the Grain cipher, accomplished by harnessing the power of deep learning models for cryptanalysis. The insights garnered from this study hold significant promise for guiding the development of more resilient encryption algorithms, thereby reinforcing the security of data transmission across diverse applications.