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A Novel Image Steganographic Method Based on Enhanced PIWT and Modified Optimal Pixel Adjustment Process

IET Image Processing, Volume 20, Issue 1, January/December 2026.
This paper proposes a novel image steganographic method based on an enhanced Pyramid Integer Wavelet Transform (PIWT) combined with a Modified Optimal Pixel Adjustment Process (MOPAP). The PIWT enables integer‐to‐integer transformation, avoiding floating‐point computations and improving its suitability for efficient implementation.
Ali Yahya Al‐Ashwal, Waled Hussein Al‐Arashi, Mohammed Mohsen Alkhawlani   +2 more
wiley   +1 more source

A Unified Adversarial Defence Framework: Diffusion‐Driven Purification with Adaptive Timestep Selection and Detection via Reconstruction Consistency Features

IET Image Processing, Volume 20, Issue 1, January/December 2026.
This study presents a unified adversarial defence framework that employs a diffusion‐driven adversarial purification method with an adaptive timestep selection mechanism, followed by adversarial image detection using a custom feature set termed reconstruction consistency features. Experimental evaluations on CIFAR‐10, CIFAR‐100 and ImageNet demonstrate
Md. Sajid Alam Chowdhury, Md. Khairul Islam, Kaushik Deb   +2 more
wiley   +1 more source

From Blind to Quantitative Steganalysis [PDF]

IEEE Transactions on Information Forensics and Security, 2009
A quantitative steganalyzer is an estimator of the number of embedding changes introduced by a specific embedding operation. Since for most algorithms the number of embedding changes correlates with the message length, quantitative steganalyzers are important forensic tools.
Tomás Pevný, Jessica J. Fridrich, Andrew D. Ker   +2 more
openaire   +2 more sources

AI Secure Watermarking Method Leveraging the Error‐Resistant Nature of Deep Learning Models

IET Image Processing, Volume 20, Issue 1, January/December 2026.
ABSTRACT The widespread use of generated media based on generative AI models, raises the risks of copyright violation and ownership conflicts. It has also introduced challenges such as deepfake misuse and unauthorised distribution of digital content. Watermarking methodologies, including embedding and tracing, have emerged as solutions for protecting ...
Arushi Chatterjee, Chittaranjan Pradhan, Hrudaya Kumar Tripathy, Tarek Gaber, Mohamed Mostafa Fouad   +4 more
wiley   +1 more source

Deep Learning–Based Image Steganography for Signal Processing and Communication Systems: A Survey of Architectures, Lossy‐Channel Robustness, and Evaluation Practices

Journal of Electrical and Computer Engineering, Volume 2026, Issue 1, 2026.
Image steganography is a signal‐processing and communication‐system problem as much as a security problem: A hidden signal must be embedded, transmitted, and recovered through visual channels while preserving image fidelity and limiting statistically detectable distortion.
Ngoc-Giau Pham, Phuoc-Hung Vo, Hong-Ngoc Tran, Pramita Mishra   +3 more
wiley   +1 more source

Features-pooling blind jpeg image steganalysis

, 2008
In this research, we introduce a new blind steganalysis in detecting grayscale JPEG images. Features-pooling method is employed to extract the steganalytic features and the classification is done by using neural network.
Leng, Chiew Kang, Josef Pieprzyk, Chiew Kang Leng, Pieprzyk, Josef   +3 more
core   +1 more source

Detecting Deepfakes Using Two‐Stream Framework Based on EfficientNet and Vision Transformer

Journal of Electrical and Computer Engineering, Volume 2026, Issue 1, 2026.
The ever‐growing threat of deepfake technology has stimulated research in deepfake forensics to identify the genuineness of media materials on the Internet. The majority of existing techniques employ the convolutional neural network (CNN) framework to identify deepfake by capturing the image’s local features.
Qiang Yang, Yijun Cai, Rong Yan, Guangbin Zhang, Gongping Yang   +4 more
wiley   +1 more source

Digital steganalysis: Computational intelligence approach [PDF]

, 2009
In this paper, we present a consolidated view of digital media steganalysis from the perspective of computational intelligence.In our analysis the digital media steganalysis is divided into three domains which are image steganalysis, audio steganalysis,
Samsudin, Azman, Din, Roshidi
core   +1 more source

A Dual‐Protection Framework for 3D Point Clouds: Robust Watermarking via RDWT‐SVD and High‐Capacity Steganography With Incremental Point Clouds

Modelling and Simulation in Engineering, Volume 2026, Issue 1, 2026.
3D point cloud models are being utilized more and more in computer vision, virtual reality, intelligent manufacturing, and cultural heritage preservation as a result of the quick advancements in computer graphics and 3D modeling technologies. Therefore, protecting the copyright and data integrity of 3D models has become an important issue.
Hui Wang, Ling Qin, Gaetano Sequenzia
wiley   +1 more source

Enhanced image‐splicing classification: A resilient and scale‐invariant approach utilizing edge‐weighted local texture features

Journal of Forensic Sciences, Volume 70, Issue 6, Page 2297-2308, November 2025.
Abstract The spread of image editing tools demonstrates how modern mixed‐media technology enables changes in digital images. Such easy access raises severe moral and legal concerns around the potential for malicious image editing. Overcoming this difficulty will need the development of innovative approaches for the quick detection of changes in high ...
Arslan Akram, Muhammad Arfan Jaffar, Javed Rashid, Salah Mahmoud Boulaaras, Muhammad Faheem   +4 more
wiley   +1 more source