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Issue title: Special Section: Iteration, Dynamics and Nonlinearity
Guest editors: Manuel Fernández-Martínez and Juan L.G. Guirao
Article type: Research Article
Authors: Ye, Kaia; * | Ng, M.b
Affiliations: [a] Zhengzhou Institute of Technology, Zhengzhou, China | [b] John Innes Ctr, Norwich Res Pk, Norwich, Norfolk, England
Correspondence: [*] Corresponding author. Kai Ye, Zhengzhou Institute of Technology, Zhengzhou 450044, China. E-mail: [email protected].
Abstract: When the current algorithm encrypts cloud computing user behavior data, it cannot effectively resist external attacks. When there are many feature data, the encryption performance is poor. To solve this problem, a secondary encryption algorithm for data based on coupled control game mechanism is proposed. The piecewise linear chaotic maps and Fibonacci sequence perturbations are utilized to obtain pseudo-random numbers and improve the key’s mapping space, and can effectively defend against threats and attacks. Based on the piecewise linear chaotic map encryption algorithm, the discrete chaotic integrated map encryption algorithm based on the coupled control game mechanism is adopted. After group-based encryption, the user behavior feature data is mapped into the encryption source-optimization evolution structure, and encrypted mapping is performed piecewisely. The encrypted data is used as the seed-derived set in the coupled control game mechanism, and the competition mechanism is adopted to perform the second discrete chaotic optimization on the encrypted data. The encrypted data ciphertext with the lowest chaotic discrete coefficient and the best game performance is selected as the output results of the coupled control game. Experimental results show that the proposed algorithm can effectively improve the encryption performance and improve the operation security of cloud computing network.
Keywords: Cloud computing, user behavior features, data encryption, secondary intelligent encryption
DOI: 10.3233/JIFS-169751
Journal: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 4, pp. 4309-4317, 2018
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