Lightweight image steganalysis with block-wise pruning [PDF]
Scientific Reports, 2023 Image steganalysis is the task of detecting a secret message hidden in an image. Deep steganalysis using end-to-end deep learning has been successful in recent years, but previous studies focused on improving detection performance rather than designing a
Eungi Hong +3 more
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Image steganalysis using active learning and hyperparameter optimization [PDF]
Scientific ReportsImage steganalysis, detecting hidden data in digital images, is essential for enhancing digital security. Traditional steganalysis methods typically rely on large, pre-labeled image datasets, which are difficult and costly to compile.
Li Bohang +9 more
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Digital Image Steganalysis: Current Methodologies and Future Challenges
IEEE Access, 2022 With the growing use of the internet and social media, data security has become a major issue. Thus, researchers are focusing on data security techniques such as steganography and steganalysis. Steganography is the approach of concealing the existence of
Wafa M. Eid +3 more
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Sensitivity of deep learning applied to spatial image steganalysis [PDF]
PeerJ Computer Science, 2021 In recent years, the traditional approach to spatial image steganalysis has shifted to deep learning (DL) techniques, which have improved the detection accuracy while combining feature extraction and classification in a single model, usually a ...
Reinel Tabares-Soto +8 more
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Color image steganalysis based on channel gradient correlation
International Journal of Distributed Sensor Networks, 2019 It is one of the potential threats to the Internet of Things to reveal confidential messages by color image steganography. The existing color image steganalysis algorithm based on channel geometric transformation measures owns higher accuracy than the ...
Yuhan Kang +5 more
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Strategy to improve the accuracy of convolutional neural network architectures applied to digital image steganalysis in the spatial domain. [PDF]
PeerJ Comput Sci, 2021 In recent years, Deep Learning techniques applied to steganalysis have surpassed the traditional two-stage approach by unifying feature extraction and classification in a single model, the Convolutional Neural Network (CNN).
Tabares-Soto R +9 more
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Deep learning for steganalysis: evaluating model robustness against image transformations. [PDF]
Front Artif IntellThis study investigates the robustness of deep learning-based steganalysis models against common image transformations because most literature has not paid enough attention to resilience assessment.
Alrusaini OA.
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Comprehensive survey on image steganalysis using deep learning
ArraySteganalysis, a field devoted to detecting concealed information in various forms of digital media, including text, images, audio, and video files, has evolved significantly over time.
Ntivuguruzwa Jean De La Croix +2 more
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Digital Image Steganalysis Based on Visual Attention and Deep Reinforcement Learning
IEEE Access, 2019 Recently, the adaptive steganography methods have been developed to embed secret information with the minimal distortion of images. As the opposite art, steganalysis methods, especially some convolutional neural network-based steganalysis methods, have ...
Donghui Hu +5 more
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Enhancing Steganography Detection with AI: Fine-Tuning a Deep Residual Network for Spread Spectrum Image Steganography [PDF]
SensorsThis paper presents an extensive investigation into the application of artificial intelligence, specifically Convolutional Neural Networks (CNNs), in image steganography detection. We initially evaluated the state-of-the-art steganalysis model, SRNet, on
Oleksandr Kuznetsov +5 more
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