Image robust adaptive steganography adapted to lossy channels in open social networks
Introduction
In recent years, the rapid development of instant messaging applications and smart devices bring new opportunities and challenges for covert communication in open social networks. Utilizing the extensiveness and popularity of image transmission in social applications, steganographers can realize covert communication with good concealment and convenience [1]. However, the processing operations that occur during the image transmission though lossy channels in open social networks often cause irreparable information loss, such as compression, noising and scaling, as shown in Fig. 1, which pose risks to reliable communication. To achieve covert communication utilize the lossy channels in open social networks, steganography methods must consider both the detection resistance against statistical features [2], and the robustness against compression, noising, and other image processing attacks [3].
To guarantee the detection resistance of stego images, current steganography algorithms are usually designed utilizing the framework of “Distortion functions + STCs” [4], [5], which can measure the embedding distortion and adaptively select the modifying position of cover elements, thereby achieving message embedding with good detection resistance. From the first proposed HUGO (Highly Undetectable steGO) [6] and S/J-UNIWARD (Spatial/JPEG UNIversal WAvelet Relative Distortion) [7] algorithms to recently proposed improved algorithms in [8], [9], many excellent adaptive steganography algorithms have emerged, which have promoted the development of image steganography techniques in terms of concealment and invisibility. However, these algorithms usually neglect possible attacks to stego images during transmission in open social networks, resulting in severely message damage after attacks and failure of covert communication [10], [11].
Concerning the message extraction accuracy after image processing attacks, robust watermarking, a typical class of information protection and authentication technology [12], has outstanding performance in both robustness and invisibility. By constructing robust embedding domains based on coefficient relationships [13], image transformation and decomposition [14], [15], the robust watermarking algorithms can embed messages without seriously affecting the image visual quality [16], and accurately detect the existence of watermarks after multiple image processing attacks, such as compression, noising, scaling and so on [17]. Unfortunately, compared with adaptive steganography, robust watermarking algorithms often cause more modifications to original images when embedding secret messages, which limits the visual quality and embedding capacity. In addition, these algorithms usually cannot guarantee the completely correct message extraction after multiple attacks, thus cannot realize reliable covert communication.
In contrast, the recently proposed robust adaptive steganography technology can take both the detection resistance and robustness into account, thus becoming a new research direction of image steganography. Utilizing the framework of “Robust domain construction + RS-STCs” [10], a series of steganography algorithms are first proposed with strong robustness against JPEG compression [18], [19], [20], which combines the advantages of adaptive steganography and robust watermarking algorithms. Subsequently, with the help of enhanced robust embedding domain or attack parameters in lossy channels, some novel robust adaptive steganography algorithms are proposed [21], [22], [23], [24], thereby improving the detection resistance [25], [26] and robustness against multiple image processing attacks at the same time. Although these algorithms significantly improved the message extraction accuracy after attacks, the lack of theoretical basis for embedding domain construction and over-reliance on channel parameters often cause the degradation of stego invisibility [27], [28] and the limitation of application scenarios. To achieve the covert communication in lossy channels of open social networks, the construction and selection of embedding domain with theoretical basis and multiple robustness is still an open issue [22], which restricts the development of robust steganography.
To this end, this manuscript mainly studies the robust embedding domain construction by analyzing compression resistance principle and the embedding channel selection utilizing image abstraction and saliency measurement, to design a novel steganography algorithm adapted to lossy channels with compression, noising and scaling attacks, which are common in social networks. The main contributions are:
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A robust embedding domain based on compression resistance principle and optimal element modification is proposed, thereby holding both robustness and invisibility.
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An imperceptible embedding channel selection method based on saliency differences is proposed, thus reducing modification in smooth area and maintaining robustness.
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A novel robust adaptive steganography method utilizing error-correcting and STC codes is proposed, which can reduce message embedding costs and enhance robustness.
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The fault tolerance of the proposed method is deduced by the constructed error model and coding characteristics, thus providing the recommended coding parameters.
The rest of this manuscript is organized as follows. In Section 2, the preliminary works are described and discussed concerning robust adaptive steganography and image salient region detection. Then, the robust embedding domain is constructed based on compression principle and optimal element modification in Section 3. Utilizing the robust image abstraction and saliency measurement, the imperceptible embedding channel selection method is proposed in Section 4. On this basis, combining with “Error-correcting + STC Codes”, the proposed algorithm is given in Section 5. After parameters discussion and selection, Section 6 tests the robustness and detection resistance of the proposed method, comparing with some state-of-the-art algorithms. In addition, the coding methods and parameters are also discussed and provided in Section 6, concerning the fault tolerance and message extraction integrity. Finally, this manuscript is concluded by Section 7.
Section snippets
Related works
In this section, previous studies about robust steganography and image saliency detection are briefly described, thereby illustrating the feasibility for designing robust steganography.
Robust domain construction by compression principle and optimal element modification
By analyzing the compression resistant principle, a robust element extraction and modification method is proposed in this section, thereby constructing a robust embedding domain with theoretical foundations and good invisibility.
Imperceptible embedding channel selection based on saliency differences
To further improve visual imperception, based on robust image abstraction and saliency measurement, an embedding channel selection method is proposed in this section, thus avoid modifications in smooth areas and improve security.
Robust adaptive steganography utilizing “Error-correcting + STC Codes”
Combining with the constructed robust domain and selected embedding channel, the compression resistant principle based adaptive steganography (CRPAS) is proposed in this section, using the “Error-correcting + STC Codes”. The specific procedures are shown in Fig. 5 and described in detail as follows.
Experimental results and analysis
In this section, the coefficient pair selection for message embedding is discussed first concerning the robustness and visual quality of stego images. On this basis, the proposed method is test and analyzed in terms of robustness, detection resistance, and communication in open social networks, compared with some state-of-the-art algorithms. Lastly, the fault tolerance of error-correcting codes is analyzed using the error model based on burst errors and decoding damage, and the recommended
Conclusions
For the robustness and security requirements of covert communication in open social networks, a novel adaptive steganography with multiple robustness and detection resistance is proposed in this manuscript, utilizing the constructed robust embedding domain and selected embedding channels. Based on compression resistance principle, the robust embedding domain is first constructed with theoretical foundation and optimal modification, thereby holding both robustness and invisibility. Then, the
CRediT authorship contribution statement
Yi Zhang: Methodology, Software, Formal analysis, Writing - original draft. Xiangyang Luo: Conceptualization, Validation, Writing - review & editing. Jinwei Wang: Investigation, Visualization. Yanqing Guo: Resources, Data curation. Fenlin Liu: Conceptualization, Supervision.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This work was supported by the National Natural Science Foundation of China [U1804263, U1736119, U1736214, U1636219, 61872448, 61772281]; the National Key Research and Development Project of China [2016YFB0801303, 2016QY01W0105]; the Science and Technology Innovation Leading Talent Program of Central Plains [214200510019]; the Science and Technology Innovation Talent Project of Henan Province [184200510018].
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