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• W2768334467 startingPage "109" @default.
• W2768334467 abstract "Abstract Chaotic synchronization has suffered from demodulating information by hackers via the public channel. Different methods have been developed to hide the contents of a message using chaotic signals. Nevertheless, many studies have shown that most of the existing methods are unreliable in the aspect of security. According to the above, in order to enhance the strength of the cryptosystem and provide greater security, we carry out double encryption which combines chaotic synchronization with RSA algorithm. In this study, a design methodology for neural-network (NN)-based secure communications in multiple time-delay chaotic (MTDC) systems is proposed to obtain double encryption via RSA algorithm and chaotic synchronization. RSA algorithm is an asymmetric encryption and its strength is based on the tremendous difficulty of factorizing two large prime numbers. Accordingly, it takes much more time to process RSA algorithm if the length of the key is much longer. A shorter key is used to decrease the processing time of RSA algorithm in this work. Nevertheless, it will result in a lower security of the cryptosystem. In order to enhance the strength of the cryptosystem, we carry out double encryption which combines chaotic synchronization with RSA algorithm. Moreover, an IGA is proposed in this study to effectively overcome the weakness of the traditional GA. On the basis of the IGA, a fuzzy controller is synthesized to not only realize the exponential synchronization, but also achieve optimal H ∞ performance by minimizing the disturbances attenuation level. Finally, a numerical example with simulations is given to illustrate the effectiveness of our approach." @default.
• W2768334467 created "2017-12-04" @default.
• W2768334467 creator A5082979225 @default.
• W2768334467 date "2018-07-01" @default.
• W2768334467 modified "2023-09-25" @default.
• W2768334467 title "Chaotic synchronization cryptosystems combined with RSA encryption algorithm" @default.
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• W2768334467 doi "https://doi.org/10.1016/j.fss.2017.10.016" @default.
• W2768334467 hasPublicationYear "2018" @default.
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