LSB Color Image Embedding Steganography Based on Cyclic Chaos

Deng, Jiayu; Tang, Mingwei; Wang, Yanting; Wang, Zhen

doi:10.1109/iccc47050.2019.9064335

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…Image steganography has two categories: spatial domain algorithms and transform domain algorithms. The spatial domain algorithms embed secret by modifying the value of the image elements, such as Least Significant Bit (LS-B) based methods [14]- [16], Pixel Value Difference (PVD) based methods [17]- [19], and so on. The transform domain algorithms embed secret by modifying the transform domain coefficients, that are, Discrete Cosine Transform (DCT) [20], variants of Discrete Wavelet Transform (DWT) [21], and Fast Fourier Transform (FFT) [22].…”

Section: Related Workmentioning

confidence: 99%

Image Steganography Based on Artificial Immune in Mobile Edge Computing With Internet of Things

Ding

Xie

et al. 2020

IEEE Access

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Mobile edge computing provides high computing power, data storage capacity and bandwidth requirements for Internet of Things (IoT) through edge servers that process data close to data sources or users. In practical, mobile edge computing can be used to implement image steganography in IoT. Considering imperceptibility, security and capacity are important indicators for image steganography, this paper propose an image steganography based on evolutionary multi-objective optimization (EMOsteg). The EMOsteg preprocesses the image through a high-pass filters bank to find noise and texture regions that are difficult to model. By perturbing the image on noise and texture regions in multiple directions, the embedded capacity is increased. By defining the imperceptibility and security as an antigen, defining the perturbation positions of the cover image as an antibody, the EMOsteg uses the artificial immune principle to heuristically obtain the perturbation population through feature extraction of the perturbation and adaptive evolution operations. And the Pareto optimal is used to find the optimal perturbation in the last generation population. The simulation experiments analyze the convergence of the algorithm and the diversity of the solutions. In simulation experiments, the MSE, PSNR and SSIM were adopted to evaluate the imperceptibility, and the results show that the MSE value of our algorithm is 0.000308, the PSNR is 82.7501 and the SSIM approaches 1, they are better than comparison algorithms. The average detection error P E under SPA was adopted to detect the security, and the results show that our algorithm is more robust against anti-SPA steganalysis. In order to evaluate the performance of real-time, the embedding time of the same secret under different algorithms were compared, and the results show that our algorithm is faster than comparison algorithms in the terminal. In summary, the proposed algorithm can maintain the image quality while resist steganalysis tools, and realize real-time processing.

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Section: Related Workmentioning

confidence: 99%

Image Steganography Based on Artificial Immune in Mobile Edge Computing With Internet of Things

Ding

Xie

et al. 2020

IEEE Access

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“…In recent studies, techniques such as pixel value difference (PVD), discrete cosine transform (DCT), least significant bit (LSB), pixel indicator technique (PIT), discrete Haar wavelet transform (DHWT), optimal pixel adjustment process (OPAP) is utilized (Xie et al 2021). These shared techniques are spatial domain and frequency domain methods used in digital image steganography (Deng et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Highly Secured Hybrid Image Steganography with an Improved Key Generation and Exchange for One-Time-Pad Encryption Method

Takaoğlu

Özyavaş

Ajlouni

et al. 2023

Afyon Kocatepe University Journal of Sciences and Engineering

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Steganography is a subject of study that has been used to hide information throughout history. In cryptology science, the information to be hidden is encrypted. Both study subjects are widely used in information security and protection. In our study, digital image steganography, which is one of the application areas of steganography, was developed and applied to hide text in the selected images. While doing this, the low bands that will hide the data using the discrete Haar wavelet transform of the images obtained first. The text to be hidden is encrypted with the one-time-pad algorithm. The key used for the encryption is transmitted to the receiver using a transmission layer based on a Highly Secured Information Exchange Algorithm. The algorithms use a randomly generated key pool maintained by both the transmitter and the receiver. A key is selected from the pool randomly by generating a random key start point for every message. The pool size and the randomness are critical factors in guaranteeing no key repetition, which is a requirement for a one-time-pad. The ciphertext and the key starting point indicator are hidden in the low bands of the pictures by utilizing the least significant bit method. The optimal pixel adjustment process was applied to the pre-stego-images, this resulted in an improvement in the results. The results obtained in this study are compared against the pre-optimal pixel adjustment process results and the results obtained through peer studies. The test results show that the proposed method outperformed all the methods in terms of peak signal-to-noise ratio, structural similarity index metric, mean absolute error, mean consequential error and the encryption key security.

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Image Encryption Based on Cyclic Chaos, PRNG and Arnold’s Cat Map

Das¹,

Pradhan²

2023

Lecture Notes in Networks and Systems

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LSB Color Image Embedding Steganography Based on Cyclic Chaos

Cited by 5 publications

References 11 publications

Image Steganography Based on Artificial Immune in Mobile Edge Computing With Internet of Things

Image Steganography Based on Artificial Immune in Mobile Edge Computing With Internet of Things

Highly Secured Hybrid Image Steganography with an Improved Key Generation and Exchange for One-Time-Pad Encryption Method

Image Encryption Based on Cyclic Chaos, PRNG and Arnold’s Cat Map

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