Abstract
This paper proposes a new hybrid algorithm for secure communication applications. The proposed algorithm includes a fuzzy brain emotional learning controller (FBELC), a recurrent cerebellar model articulation controller (RCMAC), and a robust compensator (RC). The main brain-imitated neural network controller is a combination of the RCMAC and the FBELC, which is a mathematical model that approximates the decision and emotional activity of a human brain. A fuzzy inference system is also merged into the FBELC to produce an efficient hybrid structure, then it is used for secure communication applications. The 3-dimensional (3D) Genesio chaotic system is used for audio and image secure communication systems to show the potency and performance of the proposed algorithm. In the first application, a new image encryption algorithm is proposed to enhance security for information transmission, then several standard images are applied for the chaotic synchronization of image secure communication. In the second application, the audio signal is embedded in a 3D chaotic trajectory, which is used as an encryption carrier signal, after using the proposed method for the decryption, the source signal can be retrieved. The comparisons of simulation results using security analyses and root mean square error for recent algorithms are performed to validate the performance and efficiency of the proposed hybrid algorithm. The simulation results point out that our algorithm can attain better synchronization performance, and achieve more efficient audio and image secure communications.
Highlights
Chaos is a remarkably fascinating phenomenon, which has been widely studying in the past decades [1]–[5]
It is sensitive to initial values, non-periodic, trajectory unpredictability, chaos theory is usually applied for secure communication [6], image encryption [7], signal processing [8], cryptography [9], etc
Our method efficiently reduces the correlation of pixels compared to Deoxyribonucleic acid (DNA) method [40], ciphertext diffusion in crisscross pattern [42], an improved and enhanced method based on hyperchaos [43], DNA encoding method [44], and hyperchaotic and DNA sequences method [45]
Summary
Chaos is a remarkably fascinating phenomenon, which has been widely studying in the past decades [1]–[5]. Few studies have used the combination of CMAC and BELC to apply for chaotic synchronizations, audio and image secure communications based on 3D chaotic systems. The proposed method is combined a BELC, a recurrent CMAC, and a fuzzy inference system to create the RCFBC that has the advantages of the recurrent CMAC [30] and the BELC [31] that are (1) Using external feedback via recurrent units, built-in loopback allows the network to remember the system’s past states and to learn the system parameters Based on this feature, recurrent CMAC usually shows quick response and good performance in the presence of uncertainties. The RCFBC and a robust compensator concurrently form the hybrid control system for 3D Genesio chaotic synchronization, image secure communication, and audio secure communication.
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