Open Access

ARTICLE

Coverless Information Hiding Based on the Molecular Structure Images of Material

by Yi Cao¹, Zhili Zhou¹, Xingming Sun¹, Chongzhi Gao⁴

1 School of Computer and Software, Nanjing University of Information Science and Technology, Ning Liu Road, NO. 219, Nanjing, 210044, China.
2 Jiangsu Engineering Centre of Network Monitoring, Ning Liu Road, No. 219, Nanjing, 210044, China.
3 Department of Electrical and computer Engineering, University of Windsor, 401 Sunset Avenue, Windsor, ON, Canada N9B 3P4.
4 School of Computer Science, Guangzhou University, Waihuanxi Road, No. 230, Guangzhou, 510006, China.

* Corresponding author: Chongzhi Gao, Email: .

Computers, Materials & Continua 2018, 54(2), 197-207. https://doi.org/10.3970/cmc.2018.054.197

Abstract

The traditional information hiding methods embed the secret information by modifying the carrier, which will inevitably leave traces of modification on the carrier. In this way, it is hard to resist the detection of steganalysis algorithm. To address this problem, the concept of coverless information hiding was proposed. Coverless information hiding can effectively resist steganalysis algorithm, since it uses unmodified natural stego-carriers to represent and convey confidential information. However, the state-of-the-arts method has a low hidden capacity, which makes it less appealing. Because the pixel values of different regions of the molecular structure images of material (MSIM) are usually different, this paper proposes a novel coverless information hiding method based on MSIM, which utilizes the average value of sub-image’s pixels to represent the secret information, according to the mapping between pixel value intervals and secret information. In addition, we employ a pseudo-random label sequence that is used to determine the position of sub-images to improve the security of the method. And the histogram of the Bag of words model (BOW) is used to determine the number of sub-images in the image that convey secret information. Moreover, to improve the retrieval efficiency, we built a multi-level inverted index structure. Furthermore, the proposed method can also be used for other natural images. Compared with the state-of-the-arts, experimental results and analysis manifest that our method has better performance in anti-steganalysis, security and capacity.

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Keywords

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