An Efficient Hyperchaotic based Image Encryption Model based on DNA Encoding and Bit Scrambling


  • Swetha. T. N.
  • Dr. G. M. Sreerama Reddy


In recent times data security has been given more attention in communication and storing data, especially multimedia data/image. Digital data has been utilized in wide range of application services such as for providing secure access control mechanism, payment gateway service, in providing border security control system, forensic, fraud detection and prevention and so on. Subsequently, wide interest has been shown in providing or enhancing degree of security of multimedia data. Thus, efficient cryptography model for multimedia image is most desired. The traditional cryptography mechanism such as Data encryption standard (DES), advanced encryption standard (AES) and asymmetric encryption method such as RSA are not efficient in meeting digital image security requirement due to their low encryption security efficiency. Recently, deoxyribose nucleic acid (DNA) sequences and hyperchaotic sequence are jointly used for building secure and efficient image encryption model. However, the state-of-art model are not efficient (robust) against noise and cropping attack. Since in existingmodel most digits of each pixel are not altered. For enhancing security for encrypting high dimensional images, this work use both hyperchaotic and deoxyribose nucleic acid sequence. Firstly, pseudorandom sequence is generated using hyperchaotic system. This is done to use hyperchaotic sequences for each possible cases of the cryptography process where intensity parameters of a high dimensional images are transformed to a serial binary digit stream. Then, this stream of bits is scrambled using hyperchaotic sequence. Deoxyribose nucleic acid complementation and algebraic function are conducted among the deoxyribose nucleic acid sequences and the hyperchaotic sequences for attaining a dynamic and efficient image encoding outcomes. The experimental outcome shows proposed image encryption model attain superior performance than stat-of-art model in terms of robustness against entropy, statistical, cropping, noise, plain and differential attack.