DNA encoding for RGB image encryption with memristor based neuron model and chaos phenomenon. (October 2020)

• Record Type: Journal Article
• Authors: Yildirim, Melih
• Is Part Of: Microelectronics journal. Volume 104(2020)
• Publication Date: 2020-10
• Subjects: Neuromorphic -- Memristor -- DNA encoding -- Hindmarsh-rose neuron model -- Spiking -- Chaos -- Cryptology; Microelectronics -- Periodicals; Microélectronique -- Périodiques; Microelectronics; Electronic journals; Journals - contents and abstracts; Periodicals; 621.3805
• DOI: 10.1016/j.mejo.2020.104878
• Languages: English
• ISSNs: 0959-8324

Abstract

Abstract: In this paper, a deoxyribonucleic acid (DNA) encoding algorithm with memristor based chaotic system is proposed. The study includes four different topics together which are neuron model, circuit design with memristor, chaos theory and DNA encoding based cryptology. Operational Transconductance Amplifier (OTA) based memristive Hindmarsh-Rose neuron model using three-dimensional differential equations is employed in chaotic circuit structure. Cryptographic keys obtained from suggested three-dimensional continuous time chaotic system are utilized in order to encrypt and decrypt the image. Diffusion and confusion methods are essential for cryptology. Circular shift algorithm is used as a diffusion method and logical XOR operation is preferred as a confusion method on image. Security analyses such as histogram, correlation coefficient of two adjacent pixels, information entropy, differential attack, the secret key sensitivity and the initial condition sensitivity analyses have been performed to show the performance of the encryption scheme. Analyses results reveal that the proposed encryption is robust against statistical and differential attacks and this chaotic system also exhibits the behaviour of sensitive dependence on the secret key and the initial condition. The chaotic behaviour of the suggested system has been given performing numerical analyses in MATLAB environment and doing the analog circuit analyses with LTspice simulation software.