Fuzzy Logic-based Steganographic Scheme for high Payload Capacity with high Imperceptibility

Théophile, Ingororano; De La Croix, Ntivuguruzwa Jean; Ahmad, Tohari

doi:10.1109/isdfs58141.2023.10131727

Cited by 19 publications

(3 citation statements)

References 16 publications

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“…Fuzzy logic has found its primary practical application as process controllers in numerous fields, particularly Japan and Europe [18]. In recent applications, fuzzy logic has been widely applied in metaheuristic tasks [25], [26], regularizing the environment for smart agriculture [27], [28], covering preprocessing for enhanced payload capacity in steganographic applications [29], [30]. Unlike classical logic, which is based on sharp true-false differentiations, fuzzy logic aims to emulate human logic by performing representations in non-linear ways.…”

Section: Related Work a Fuzzy-based Edge Detection Algorithmsmentioning

confidence: 99%

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Enhancing Secret Data Detection Using Convolutional Neural Networks With Fuzzy Edge Detection

Croix,

Ahmad,

Han

2023

IEEE Access

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Progress in Deep Learning (DL), particularly Convolutional Neural Networks (CNNs), has significantly improved the accuracy of steganographic image detection. However, the applications of CNNs have several challenges, mainly due to insufficient dataset quality and quantity, the heightened imperceptibility of low payload capacities, and suboptimal feature learning procedures. This paper proposes an enhanced secret data detection approach with a CNN architecture that includes convolutional, depth-wise, separable, pooling, and spatial dropout layers. An improved fuzzy Prewitt approach is employed for pre-processing the images prior to being fed into the CNN. Experimental results show a significant outperformance over the state-of-the-art methods.

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Section: Related Work a Fuzzy-based Edge Detection Algorithmsmentioning

confidence: 99%

“…The arrangement of the convolutional layers during this phase is as such: maintaining "same" padding and utilizing strides of (1,1). This setup utilizes 30 filters, the details of which are expounded upon later, and employs a 𝟑 × 𝑻𝒂𝒏𝑯 activation function mathematically expressed in (30).…”

Section: ) Preprocessing Partmentioning

confidence: 99%

Enhancing Secret Data Detection Using Convolutional Neural Networks With Fuzzy Edge Detection

Croix,

Ahmad,

Han

2023

IEEE Access

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“…Image steganography is a technique used in secret communication to hide confidential data within ordinary cover media such as images [1], video [2], audio [3], and text [4]. In digital images, the modified pixel values in stego images are subtly altered, making them difficult to discern from the original images [5][6][7][8]. With image steganalysis, the objective is to identify the traces of embedding or even attempt to recover the concealed information in a reverse steganography process [9], as illustrated in Fig.…”

Section: Introductionmentioning

confidence: 99%

Pixel-block-based Steganalysis Method for Hidden Data Location in Digital Images

2023

IJIES

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Concealing confidential data within digital multimedia, also called steganography, has been crucial for safeguarding data. However, steganalysis techniques are best known for compromising these data concealment methods. The convolutional neural network (CNN) yielded better performance over the previously suggested techniques based on machine learning for steganalysis. Although the current approaches show promising outcomes, they encounter challenges in locating the secret data. This paper introduces a CNN architecture with a key idea to enhance the accuracy of identifying the precise hidden data location. Our method novelty is based on reducing image features and network parameters via customized feature allocation and convolutional kernels optimization and enhancing classification accuracy by optimizing the kernels combined with back-forward gradient descent. Our experimental results show improvements over the existing works with the accuracy under payload capacity of 0.4 bpp from 83.01% to 98.78% for S-UNIWARD and 87.19% to 97.93% for WOW.

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Comprehensive survey on image steganalysis using deep learning

Croix,

Ahmad,

Han

2024

Array

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Fuzzy Logic-based Steganographic Scheme for high Payload Capacity with high Imperceptibility

Cited by 19 publications

References 16 publications

Enhancing Secret Data Detection Using Convolutional Neural Networks With Fuzzy Edge Detection

Enhancing Secret Data Detection Using Convolutional Neural Networks With Fuzzy Edge Detection

Pixel-block-based Steganalysis Method for Hidden Data Location in Digital Images

Comprehensive survey on image steganalysis using deep learning

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