基于神经网络与复合离散混沌系统的双重加密方法

Translated title of the contribution: Double Encryption Method Based on Neural Network and Composite Discrete Chaotic System

Chenglong Xiao, Ying Sun, Bangjiang Lin, Xuan Tang, Shanshan Wang, Min Zhang, Yufang Xie, Lingfeng Dai, Jiabin Luo

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Orthogonal Frequency Division Multiplexing(OFDM) is widely used in wireless communication systems, and its data transmission security has certain practical significance. A double encryption scheme is proposed which enhances the confidentiality of the OFDM communication system and can prevent brute force attacks significantly. Specifically, the first encryption is achieved by using neural network to generate the scrambling matrix, and the second encryption is implemented by chaotic sequence generating by composite discrete chaotic system based on Logistic mapping and Sine mapping. Moreover, it has larger secret key space compared with the single one-dimensional Logistic mapping chaotic system. The performance of double encryption is measured by verifying its chaotic characteristics and randomness (Lyapunov exponent and NIST) as well as its security performance in simulation. The results show that Lyapunov index is increased to 0.9850, and the maximum P-value in the NIST test is 0.9995 by using the proposed double encryption in this paper. It indicates such double encryption significantly improve the confidentiality of the OFDM communication system without affecting the transmission performance.

Translated title of the contributionDouble Encryption Method Based on Neural Network and Composite Discrete Chaotic System
Original languageChinese (Traditional)
Pages (from-to)687-694
Number of pages8
JournalDianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
Volume42
Issue number3
DOIs
StatePublished - 1 Mar 2020
Externally publishedYes

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