Journal
NEUROCOMPUTING
Volume 275, Issue -, Pages 1318-1332Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2017.09.068
Keywords
Partitioned cellular automata; Image encryption; Strict avalanche criterion; Parallel encryption
Categories
Funding
- National Natural Science Foundation of China [61472464]
- Natural Science Foundation of CQ CSTC [cstc2016jcyjA0276, cstc2015jcyjA0554, cstc2015jcyjA40025]
- Fundamental Research Funds for the Central Universities [106112016CDJXY180006]
- National Social Science Foundation of China [14CTQ026]
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Image encryption techniques aims to protect the content of image with higher efficiency and security than conventional cryptographic methods by making use of special properties of image. This paper presents an image encryption model based on two-dimensional partitioned cellular automaton. The model has the same topology as a digital image and is flexible to images with different color depth; it is efficient as only substitution and permutation operations are involved; the properties of cellular automata make the model easy for Very Large Scale Integration (VLSI) implementation. Moreover, unlike most known image encryption algorithms, this model can support parallel computing. A probability cellular automaton called coloring model, is proposed to study the sensitivity of the encryption model. It shows that the model meets the global strict avalanche criterion in at most M + N + 7 rounds of encryption for an M x N image. Several approaches are proposed to estimate the minimal number of rounds to fulfill the global strict avalanche criterion; simulation shows that the maximal error is only one round. An image encryption algorithm based on this model is presented, which is demonstrated by experiments to own the properties of randomness and sensitivity. (C) 2017 Elsevier B.V. All rights reserved.
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