FPGA Implementation of DNA Computing and Genetic Algorithm Based Image Encryption Technique

In the digital age, an increasing dependency of humans on digital technologies is much prevalent. A high demand in securing the private and confidential data is essential, which would otherwise lead to mishandling and misuse of personal information for ulterior motives. To avoid such vulnerabilities many Cryptographic and stenographic techniques were developed over the past decades. Though such existing schemes provided satisfactory shielding, high computational cost, increased processing time, low embedding capacity, and low imperceptibility, renders it as unsuitable for applications requiring high security and high speed such as medical data security. A hybrid DNA computing technology combined with a genetic algorithm is developed in this work to cater for medical image encryption, which will address the aforementioned limitations. The suggested approach converts plaintext information into binary by first mapping it to the DNA sequence. The binary information is then embedded in the cover image using genetic algorithm to yield a stego image. Elliptic Curve Cryptographic hardware (ECC) encrypts the generated stego image, providing a more secure means of storage/communication. The suggested hardware system is implemented in the Zynq 7000 FPGA device, which occupied a comparatively low overall LUT and DSP slices of around 5796 and 19 respectively.