Discrete Multi-graph Hashing for Large-Scale Visual Search

Xiang, Lingyun; Shen, Xiaobo; Qin, Jiaohua; Wei, Hao

doi:10.1007/s11063-018-9892-7

Cited by 68 publications

(34 citation statements)

References 24 publications

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“…With the development of communication technology and the coming of information age, people are more and more aware of the important role of information security [71][72][73][74][75][76], and the research of various security protection has become the current research hotspot [77][78][79][80][81][82]. As an important part of information security transmission, random number generator (RNG) has been paid more and more attention.…”

Section: Introductionmentioning

confidence: 99%

Chaos-Based Application of a Novel Multistable 5D Memristive Hyperchaotic System with Coexisting Multiple Attractors

Liu

Qian

et al. 2020

Complexity

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Novel memristive hyperchaotic system designs and their engineering applications have received considerable critical attention. In this paper, a novel multistable 5D memristive hyperchaotic system and its application are introduced. The interesting aspect of this chaotic system is that it has different types of coexisting attractors, chaos, hyperchaos, periods, and limit cycles. First, a novel 5D memristive hyperchaotic system is proposed by introducing a flux-controlled memristor with quadratic nonlinearity into an existing 4D four-wing chaotic system as a feedback term. Then, the phase portraits, Lyapunov exponential spectrum, bifurcation diagram, and spectral entropy are used to analyze the basic dynamics of the 5D memristive hyperchaotic system. For a specific set of parameters, we find an unusual metastability, which shows the transition from chaotic to periodic (period-2 and period-3) dynamics. Moreover, its circuit implementation is also proposed. By using the chaoticity of the novel hyperchaotic system, we have developed a random number generator (RNG) for practical image encryption applications. Furthermore, security analyses are carried out with the RNG and image encryption designs.

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Section: Introductionmentioning

confidence: 99%

Chaos-Based Application of a Novel Multistable 5D Memristive Hyperchaotic System with Coexisting Multiple Attractors

Liu

Qian

et al. 2020

Complexity

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“…with audio, video, and other media types as covers. 32 It may be a potential idea to search similar cover media 33 and apply the data learning 34 to recognize the stego positions.…”

Section: Resultsmentioning

confidence: 99%

Payload location for JPEG image steganography based on co-frequency sub-image filtering

Wang

Yang

Wang

et al. 2020

International Journal of Distributed Sensor Networks

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In digital steganography, due to difficulties estimating the JPEG cover image, it is still very hard to accurately locate the hidden message embedded in a JPEG image. Therefore, this study proposes a payload location method for a category of pseudo-random scrambled JPEG image steganography. In order to estimate the quantized discrete cosine transform coefficients in the cover JPEG image, a cover JPEG image estimation method is proposed based on co-frequency sub-image filtering. The proposed payload location method defines a general residual, uses the estimated cover JPEG image to compute the residuals, and then employs the mean residuals of multiple stego images embedded along the same path to distinguish the stego positions. The proposed cover JPEG image estimation method constructs 64 co-frequency sub-images, and then filters the sub-image to estimate the cover JPEG image. Finally, using these methods, payload location algorithms are designed for two common JPEG image steganography algorithms: JSteg and F5. Experimental results show that the proposed location algorithms can effectively locate the stego positions in both JSteg and F5 steganography when the investigator possesses multiple stego images embedded along the same path. In addition, the location results can also be used to recover the steganography key to extract the embedded secret messages.

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“…Therefore, we would try to fuse more effective locating algorithms by the stronger learning method [Xiang, Zhao, Li et al (2018)]. Additionally, we may search the images with the similar contents on the Internet [Xiang, Shen, Qin et al (2018)], and use them as references to estimate the cover images.…”

Section: Resultsmentioning

confidence: 99%

Locating Steganalysis of LSB Matching Based on Spatial and Wavelet Filter Fusion

Yang¹,

Wang²,

Lin³

et al. 2019

Computers, Materials &Amp; Continua

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For the case of that only a single stego image of LSB (Least Significant Bit) matching steganography is available, the existing steganalysis algorithms cannot effectively locate the modified pixels. Therefore, an algorithm is proposed to locate the modified pixels of LSB matching based on spatial and wavelet filter fusion. Firstly, the validity of using the residuals obtained by spatial and wavelet filtering to locate the modified pixels of LSB matching is analyzed. It is pointed out that both of these two kinds of residuals can be used to identify the modified pixels of LSB matching with success rate higher than that of randomly guessing. Then, a method is proposed to measure the correlation between the results of two locating algorithms. Statistical results show that there are low correlations between the locating results of spatial filter based algorithm and wavelet filter based algorithm. Then these two kinds of residuals are fused by the voting method to improve the locating performance. The experimental results show that the proposed fusion algorithm can effectively improve the locating accuracy for the modified pixels of LSB matching.

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Discrete Multi-graph Hashing for Large-Scale Visual Search

Cited by 68 publications

References 24 publications

Chaos-Based Application of a Novel Multistable 5D Memristive Hyperchaotic System with Coexisting Multiple Attractors

Chaos-Based Application of a Novel Multistable 5D Memristive Hyperchaotic System with Coexisting Multiple Attractors

Payload location for JPEG image steganography based on co-frequency sub-image filtering

Locating Steganalysis of LSB Matching Based on Spatial and Wavelet Filter Fusion

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