LSB Pseudorandom Algorithm for Image Steganography Using Skew Tent Map

Pichardo-Méndez, J. L.; Palacios-Luengas, Leonardo; Martínez-González, Ricardo Francisco; Jiménez-Ramírez, Omar; Vázquez-Medina, Rubén

doi:10.1007/s13369-019-04272-0

Cited by 6 publications

(4 citation statements)

References 58 publications

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“…Similarly, [33] www.ijacsa.thesai.org uses Pseudo-Random Number Generator (PRNG) to choose a pixel for the embedding process. Three PRNGs are generated with the help of the Skew Tent Map (SKTM) in [34]. They are employed to scramble secret messages before insertion, choose an embedding color channel, and select a pixel location with a particular Red-Green-Blue (RGB) channel.…”

Section: A Randomization Based Techniquesmentioning

confidence: 99%

A Review on Security Techniques in Image Steganography

Ghoul¹,

Sulaiman²,

Shukur³

2023

IJACSA

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Given the increased popularity of the internet, the exchange of sensitive information leads to concerns about privacy and security. Techniques such as steganography and cryptography have been employed to protect sensitive information. Steganography is one of the promising tools for securely exchanging sensitive information through an unsecured medium. It is a powerful tool for protecting a user's data, wherein the user can hide messages inside other media, such as images, videos, and audios (cover media). Image steganography is the science of concealing secret information inside an image using various techniques. The nature of the embedding process makes the hidden information undetectable to human eyes. The challenges faced by image steganography techniques include achieving high embedding capacity, good imperceptibility, and high security. These criteria are inter-related since enhancing one factor undermines one or more others. This paper provides an overview of existing research related to various techniques and security in image steganography. First, basic information in this domain is presented. Next, various kinds of security techniques used in steganography are explained, such as randomization, encryption, and region-based techniques. This paper covers research published from 2017 to 2022. This review is not exhaustive and aims to explore state-of-the-art techniques applied to enhance security, crucial issues in the domain, and future directions to assist new and current researchers.

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Section: A Randomization Based Techniquesmentioning

confidence: 99%

A Review on Security Techniques in Image Steganography

Ghoul¹,

Sulaiman²,

Shukur³

2023

IJACSA

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“…To such purpose, we identify the conditions for which the chaotic maps can generate periodic sequences, as well as those conditions for which they can generate aperiodic sequences. In order to offer this analysis of behavior (periodic or aperiodic), in a similar way to Palacios-Luengas et al [14] and Pichardo-Méndez et al [67], we identify the chaos annulling conditions in the proposed chaotic maps, and we calculate their bifurcation diagrams and Lyapunov exponents.…”

Section: Behavior Analysismentioning

confidence: 99%

“…But, the FC does not have fixed points and stability islands at parameter domains of chaotic behavior when µ < α. In a similar way to Palacios-Luengas et al [14] and Pichardo-Méndez et al [67], the statistical distribution of the sequences produced by both chaotic maps can be estimated through the stationary statistical distribution by using the Birkhoff's Ergodicity Theorem [70], and considering that the evolution of a set of initial condition must be studied when the chaotic system is applied to it. Now, as an example, in Figure 5 we show the trajectory diagrams of both chaotic systems when α = 3.0 considering 10,000 iterations.…”

Section: Stmmentioning

confidence: 99%

Function Composition from Sine Function and Skew Tent Map and Its Application to Pseudorandom Number Generators

et al. 2021

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In cryptography, the pseudorandom number sequences must have random appearance to be used in secure information systems. The skew tent map (STM) is an attractive map to produce pseudorandom sequences due to its easy implementation and the absence of stability islands when it is in chaotic behavior. Using the STM and sine function, we propose and analyze a function composition to propose a pseudorandom number generator (PRNG). In the analysis of the function composition, we use the bifurcation diagram and the Lyapunov exponent to perform a behavioral comparison against the STM. We show that the proposed function composition is more sensitive to initial conditions than the STM, and then it is a better option than the STM for cryptography applications. For the proposed function we determine and avoid the chaos annulling traps. The proposed PRNG can be configured to generate pseudorandom numbers of 8, 16 or 32 bits and it can be implemented on microcontrollers with different architectures. We evaluate the pseudorandomness of the proposed PRNG using the NIST SP 800-22 and TestU01 suites. Additionally, to evaluate its quality, we apply tests such as correlation coefficient, key sensitivity, statistical and entropy analysis, key space, linear complexity, and speed. Finally, we performed a comparison with similar PRNGs that produce pseudorandom sequences considering numbers of 8 and 32 bits. The results show that the proposed PRNG maintains its security regardless of the selected configuration. The proposed PRNG has five important features: easy implementation, configurable to produce number with 8, 16 or 32 bits, high processing speed, high linear complexity, and wide key space. These features are necessary for cryptographic systems.

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“…By translating the difference of the two values, followed by the replacement of the cover pixels, produces Stego-image. The author in [50] proposed an LSB based Steganography method to hide secret data in digital images in a pseudorandom fashion via three chaotic noise generators based on the skew tent chaotic map. The author in [51] suggests utilizing a bit reversal method based on 2 schemes for improving the quality of Stego-image.…”

Section: Review Of the Literaturementioning

confidence: 99%

Prudently Secure Information Theoretic LSB Steganography for Digital Grayscale Images

Rafat¹

2020

IJACSA

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The endangerment of online data breaches calls for exploring new and enhancing existing sneaky ways of clandestine communication to tailor those to match the present and futuristic technological and environmental needs, to which malicious intruders wouldn't have an answer. Cryptography and Steganography are the two distinct techniques that, for long, have remained priority choices for hiding vital information from the unauthorized. But the visibility of the encrypted contents makes these vulnerable to attack. Also, the recent legislative protection agreed to law enforcement authorities in Australia to sneak into pre-shared cryptographic secret keys (PSKs) shall have a devastating impact on the privacy of the people. Hence, the need of the hour is to veil in the encrypted data underneath the cover of Steganography, whose sole intent is to hide the very existence of information. This research endeavor enhances one of the most famous images Steganography technique called the Least Significant Bit (LSB) Steganography, from the security and information-theoretic standpoint by taking a known-cover and known-message attack scenario. The explicit proclamation of this research endeavor is that the security of LSB Steganography lies in inducing uncertainty at the time of bit embedding process. The test results rendered by the proposed methodology confers on the non-detectability and imperceptibility of the confidential information along with its strong resistance against LSB Steganalysis techniques.

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LSB Pseudorandom Algorithm for Image Steganography Using Skew Tent Map

Cited by 6 publications

References 58 publications

A Review on Security Techniques in Image Steganography

A Review on Security Techniques in Image Steganography

Function Composition from Sine Function and Skew Tent Map and Its Application to Pseudorandom Number Generators

Prudently Secure Information Theoretic LSB Steganography for Digital Grayscale Images

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