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A Digital Image Encryption Algorithm Based on Hyper-chaotic Cellular Neural Network

100%

Peng J. , Zhang D. , Liao X.

2009

tom Vol. 90, nr 3

269-282

Using Chaotic characteristics of dynamic system is a promising direction to design cryptosystems that play a pivotal role in a very important engineering application of cognitive informatics, i.e., information assurance and security. However, encryption algorithms based on the lowdimensional chaotic maps face a potential risk of the keystream being reconstructed via return map technique or neural network method. In this paper, we propose a new digital image encryption algorithm that employs a hyper-chaotic cellular neural network. To substantiate its security characteristics, we conduct the following security analyses of the proposed algorithm: key space analysis, sensitivity analysis, information entropy analysis and correlation coefficients analysis of adjacent pixels. The results demonstrate that the proposed encryption algorithm has desirable security properties and can be deployed as a cornerstone in a sound security cryptosystem. The comparison of the proposed algorithm with five other chaos-based image encryption algorithms indicates that our algorithm has a better security performance.

Triterpenoid Acids from Kadsura ananosma

75%

Chen Y. , Song X. , Hai N. , Fang A. , Bi Y. , Liao X.

2006

tom Vol. 80, nr 10

1677-1681

Ananosic acid D, a new 18 (1312) abeo lanostane triterpenoid acid was isolated from the stem barks of Kadsura ananosma and assigned the structure 3-hydroxy-18 (1312) abeo lanost-7 (8), 12 (18), 24 (Z)-trien-26-oic acid (1) by spectroscopic analysis including HR-ESI-MS and 2D-NMR. In addition, known lanostane triterpenoid acids 24(E)-3-oxo- lanosta-8, 24-dien-26-oic acid (2) and anwuweizic acid (3) were also obtained from this species. 2 was obtained as a new natural product and 3 was isolated from the plant for the first time.