Abstract
Recently, compressive sensing-based encryption methods which combine sampling, compression and encryption together have been proposed. However, since the quantized measurement data obtained from linear dimension reduction projection directly serve as the encrypted image, the existing compressive sensing-based encryption methods fail to resist against the chosen-plaintext attack. To enhance the security, a block cipher structure consisting of scrambling, mixing, S-box and chaotic lattice XOR is designed to further encrypt the quantized measurement data. In particular, the proposed method works efficiently in the parallel computing environment. Moreover, a communication unit exchanges data among the multiple processors without collision. This collision-free property is equivalent to optimal diffusion. The experimental results demonstrate that the proposed encryption method not only achieves the remarkable confusion, diffusion and sensitivity but also outperforms the existing parallel image encryption methods with respect to the compressibility and the encryption speed.









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Notes
Liao et al. [15] claimed that the full diffusion could be achieved even after the first round of encryption. However, their experiment in diffusion performance evaluation was not impartial. If one changes the original image pixel in the second quadrant, at least three rounds of encryption were necessary. Therefore, the property that full diffusion could be achieved after the first round encryption was just a best case. It should be bear in mind that when evaluating the security, only the worst boundary can be taken as a result.
The necessary round is defined as the minimum round to achieve the full confusion and diffusion.
Definition of unit throughput. Assume that the workload allocated to a processor is w, and the processing capacity of this processor is c. The unit throughput is defined as w/c.
Here, (m, n) is the coordinate of a quantized measurement within a block, while coordinate printed in the bold font (m, n) stands for the position of a block.
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Acknowledgment
The second author acknowledges the support provided by Grant NRF-2011-013-D00121 from the National Research Foundation of Korea.
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Huang, R., Rhee, K.H. & Uchida, S. A parallel image encryption method based on compressive sensing. Multimed Tools Appl 72, 71–93 (2014). https://doi.org/10.1007/s11042-012-1337-0
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DOI: https://doi.org/10.1007/s11042-012-1337-0