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In order to improve the security and robustness of the Information Steganography Algorithm under strictly controlled environment, a new algorithm of modification-free steganography based on image and big data is introduced in this paper. In the proposed algorithm, a mapping relationship between the hot image entropy and the secret information is constructed and the payload information is expressed by the mapping relation. At the same time, turbo code is introduced in order to improve robustness, the hot image comes from Internet image big data, and the library of hot image is established. The performance of the proposed algorithm is analyzed using simulation experiment. Because of its none-modifying on carrier image, the results of experiment show that the proposed algorithm can achieve good performance in robustness analysis, dimension scaling attack, and rotation attack. In particular, in the test of dimension scaling attack and the rotation attack, the rate of data recovering can be over 95%. The proposed algorithm can be very valuable in the covert communication which requires high security and low volume, for example, the key exchange of symmetric encryption system.

At present, the transmission of important data on the secure communication mainly relies on the cryptography. Cryptography techniques are aimed at encrypting the data in order to ensure its security, thus making it incomprehensible for an adversary. However, the encryption technology has an unavoidable shortage that it clearly indicates the existence of the important data and then easily attracts the attacker’s attention.

On the other hand, steganography seeks to provide a covert communication channel between two parties. A common class of steganographic algorithms embeds the secret message in cover works such as images, video, audio, or text. The combination of cover work and secret message is referred to as the stego work and a goal of all steganographic algorithms is to ensure imperceptibility, robustness, capacity, and security. Digital images as important carrier information are widely used in steganography. Presently steganography has achieved lots of research results, mainly in spatial and frequency domain of the image [

In this paper, the modification-free steganography algorithm based on image information entropy (MFSA, modification-free steganography algorithm) is proposed, which integrates big data and turbo coding technology. The MFSA establishes a relationship between the image features and the payload information. Through collecting, filtering, and cleaning of big data of network image, these images were divided into different classes according to the relevance of the content of the image, such as landscapes, cars, and small animals. The purpose of classification is to avoid noncooperative concerns. Then, we extract the entropy of the selected image and establish entropy matrix. Finally, the random occult information is mapped onto images according to certain algorithms, so as to construct a complete feature library; thus, we can conduct secret communication without modifying the original images. Because the selected images are hot, highly relative, they will not draw the attention of noncooperative side, and a truly safe and secret communication can be achieved. At the same time, the MFSA also uses error correction coding to further improve the robustness of the secret communication system.

The rest of the paper is organized as follows. Section

Given the lack of imperceptible yet robust steganography algorithms, the proposed algorithm adopts a different approach to achieve steganography. The overall block diagram of random number visualization representation system is shown in Figure

Block diagram of random number visualization expression system.

The random number at the sending end is encrypted to the corresponding ciphertext information. Because the information may be affected by the noise in the process of transmitting, which will result in the error of the binary information, the turbo error correction coding technique is used for correction in the system. Then the turbo encoded information sequence will be the business information of the sending side. Big data acquisition system based on the Java environment is a system that acquires the hot image from network, using network crawler [

Suppose that a single image has a capacity of

There are some features of the image such as color, brightness, histogram, and entropy; by extracting and quantifying, the certain image can express some binary bit sequences. However, some image feature space such as histogram has high dimensionality and poor antinoise ability. The image information entropy is a quantitative description of the image characteristics. It can be seen from the information theory that the information entropy can represent the amount of information contained in the image. From the perspective of image information entropy, the mapping relation between the entropy and the payload information is constructed in this paper, the information entropy of the image is used to represent the payload information, and the zero-steganography covert communication is achieved. Later, the construction method of image information entropy matrix is introduced in detail and the basic principles and implementation of the algorithm will be discussed.

The information entropy is defined as the mathematical expectation of random variables

In (

16 × 16 grid description of image.

The

Section

The flowchart of MFSA algorithm.

(1) The image is mapped onto a grid with a resolution of 16

(2) Derive the eigenvalue of the entropy matrix, and take the eight largest values to get the eigenvalue vector

(3) The eigenvalue vector is quantized to obtain random number

(4) The extracted random number

Generally, covert communication implements transmission with the help of the public network link. Although the MFSA algorithm itself has a high fraudulence and concealment because of its characteristics of modification-free steganography, this algorithm incorporates turbo error correction coding technology to further improve the robustness of the system considering the security and complexity of public links.

The turbo code is used to improve the robustness performance of the system and reduce the bit error rate of transmission due to its excellent error correction performance. Turbo code is a high-performance error correction. The principle and performance of turbo code coding are described in detail in [

The equation

The QPP interweaver uses some particular quadratic polynomial to make them satisfy certain conditions and become QPP structure. So the most critical problem is to solve the polynomial coefficients

The coefficient of DPP interweaver permutation multinomial.

| 32 | 64 | 128 | 256 | 512 |
---|---|---|---|---|---|

| 3 | 7 | 19 | 7 | 7 |

| 10 | 12 | 42 | 16 | 18 |

The parameters of turbo coding.

Code length | Bit rate | Interweaving method | Decoding | Iterations | Production matrix |
---|---|---|---|---|---|

32 64 128 | 0.8 | Pseudo-random intertwined | Log-MAP | 12 | ( |

It is known that the statistical analysis of the original carrier is a security risk of the covert communication, and the robustness of the carrier is also an important factor in the secure communication. So this paper designed three experiments and an analysis; the antistatistical analysis ability, the antiscale interference ability, and the antirotation attack capability of the MFSA algorithm are tested, respectively. The safety performance of this MFSA algorithm is analyzed. In the experiment, the MFSA algorithm uses a size of 16 × 16 grid descriptor. The basic characteristics of the image are mainly concentrated in the larger 5 to 8 eigenvalues, which contains information accounted for more than 90% of the total eigenvalue vector. So the experiment takes the larger 8 eigenvalues; after quantization, the length of the binary vector that can be mapped to a single image is 32 bits.

In experiment 1, the immune to statistical analysis was tested between the CSFA algorithm and the proposed algorithm in the literature [

Literature [

Due to the little payload, from the visual point of view, no difference was found between Figures

The matrix of the original image and confidential image in literature [

Since the essence of the literature [

However, the MFSA algorithm is based on the idea of no zero modification through the mapping method to express the secret information. Because it does not make any changes, it is very effective in antistatistical analysis, especially the statistical analysis of known vectors. In addition, because there is no embedded information, the original picture will not show any change, so it will not be due to visual anomalies caused by noncooperation side of the vigilance.

In experiment 2, the MFSA algorithm immune to scale attack was tested. As shown in Figure

Gray scale image of different scale. (a) Image resolution, 1024 × 1024. (b) Image resolution, 512 × 512. (c) Image resolution, 256 × 256. (d) Image resolution, 128 × 128.

The MFSA algorithm is used to demapping the original image and images with varying degrees of scaling attack, as much as possible to restore the random number it represents. The 32-bit random number vector was recovered from graph (b)

Statistical analysis of attack at different scale.

Figure | Figure | Figure | Figure | |
---|---|---|---|---|

| 0 | 0 | 3.125 | 6.25 |

| 0 | 0 | 1.25 | 3.125 |

As can be seen from Figure

In experiment 3, the MFSA algorithm immune to the rotation attack was tested. As shown in Figure

Different angle rotation of the original secret image. (a) Original secret image. (b) Rotation of 90 degrees anti-counterclockwise of the original secret image. (c) The original secret image horizontally mirrored and vertically mirrored. (d) Rotation of 270 degrees anti-counterclockwise of the original secret image. (e) The original secret image horizontally mirrored. (f) Rotation of 90 degrees anti-counterclockwise and the original secret image vertically mirrored. (g) The original secret image vertically mirrored. (h) Rotation of 270 degrees anti-counterclockwise and the original secret image vertically mirrored.

Perform 100 independent tests on different “carrier” images; according to the method in experiment 2, the inverse mapping of the original “carrier” image is subjected to different angles of rotation after the attack image is obtained. The result of statistical analysis is shown in Table

Results of statistical analysis of attack at different rotation angles.

Figure | Figure | Figure | Figure | Figure | Figure | Figure | Figure | |
---|---|---|---|---|---|---|---|---|

| 0 | 7.375 | 0 | 5.375 | 3.125 | 7.375 | 3.125 | 8.375 |

| 0 | 4.125 | 0 | 3.125 | 2.125 | 5.225 | 1.125 | 6.125 |

From the table, the original “carrier” images subjected to varying degrees of rotation attacks can be seen, the demapping data was recovered, and the data bit error rate remained at about 95%. In particular, as shown in Figure

The proposed MFSA algorithm is based on zero modification of the carrier image and it expresses the secure information by using the mapping relationship rather than embedding method, which conceals the existence of the covert communication and has a decisive effect on avoiding the nonpartner’s doubt and monitoring. Besides, the MFSA algorithm itself has a certain level of safety.

The safety performance of the MFSA algorithm is dominated by two keys:

Based on the idea of zero modification of the carrier image, the MFSA algorithm is proposed in this paper; the mapping relationship between the image information entropy and information is used to express the secure information. And the network image search engine is used to obtain the “appropriate” image from the big data of image; the big data parallel processing method as the technical support. The mathematical reasoning and the result of experiment demonstrate the proposed MFSA algorithm which has a good performance on the immune statistical analysis and some attacks. Turbo coding technology improves the system robustness and security; the simulation results showed the noise immunity of our method and this method can resist the scale and rotation attacks. Even if the nonpartner cracks the secret communication channel, and the communication “carrier” is intercepted, the nonpartner cannot judge whether the "carrier" is secret image and cannot get the content of communication. It is very suitable for the covert communication with smaller capacity and high security level, such as the transmission of security system keys, key figures, time, location, and other information transmissions.

The authors declare that there are no conflicts of interest regarding the publication of this paper.

This work was supported by the Natural Science Foundation of China and China General Technology Research Institute (U1736121).