Results 151 to 160 of about 6,282 (220)
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IEEE Transactions on Information Forensics and Security, 2020
For steganalysis, many studies showed that convolutional neural network (CNN) has better performances than the two-part structure of traditional machine learning methods.
Ru Zhang +3 more
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For steganalysis, many studies showed that convolutional neural network (CNN) has better performances than the two-part structure of traditional machine learning methods.
Ru Zhang +3 more
semanticscholar +1 more source
IEEE Transactions on Information Forensics and Security, 2008
In this paper, we describe a method for attacking Yet Another Steganographic Scheme (YASS), which is designed to be a very secure JPEG steganographic algorithm. The success of YASS is attributed to its innovation in embedding, i.e., hiding data in embedding host blocks whose locations are randomized. However, we find that the locations of the embedding
Bin Li 0011, Yun Q. Shi 0001, Jiwu Huang
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In this paper, we describe a method for attacking Yet Another Steganographic Scheme (YASS), which is designed to be a very secure JPEG steganographic algorithm. The success of YASS is attributed to its innovation in embedding, i.e., hiding data in embedding host blocks whose locations are randomized. However, we find that the locations of the embedding
Bin Li 0011, Yun Q. Shi 0001, Jiwu Huang
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Linguistic Steganalysis Toward Social Network
IEEE Transactions on Information Forensics and Security, 2023With the rapid development of the internet and social media, linguistic steganography can be easily abused in social networks to make considerable damage to varied aspects like personal privacy, network virus and national defense. Currently, considerable
Jinshuai Yang +4 more
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How to Pretrain for Steganalysis
Proceedings of the 2021 ACM Workshop on Information Hiding and Multimedia Security, 2021In this paper, we investigate the effect of pretraining CNNs on ImageNet on their performance when refined for steganalysis of digital images. In many cases, it seems that just 'seeing' a large number of images helps with the convergence of the network during the refinement no matter what the pretraining task is.
Jan Butora +2 more
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Linguistic Steganalysis in Few-Shot Scenario
IEEE Transactions on Information Forensics and Security, 2023Due to the widespread use of text in cyberspace, linguistic steganography, which hides secret information into normal texts, develops quickly in these years.
Huili Wang +4 more
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Steganalysis of AI Models LSB Attacks
IEEE Transactions on Information Forensics and Security, 2023Artificial intelligence has made significant progress in the last decade, leading to a rise in the popularity of model sharing. The model zoo ecosystem, a repository of pre-trained AI models, has advanced the AI open-source community and opened new ...
Daniel Gilkarov, Ran Dubin
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RLS-DTS: Reinforcement-Learning Linguistic Steganalysis in Distribution-Transformed Scenario
IEEE Signal Processing Letters, 2023When the data undergo a distribution change, existing linguistic steganalysis often struggles to effectively capture the statistical characteristics of the transformed cover or stego, resulting in a drop in performances.
Yihao Wang, Ru Zhang, Jianyi Liu
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Text Steganalysis Based on Hierarchical Supervised Learning and Dual Attention Mechanism
IEEE/ACM Transactions on Audio Speech and Language Processing, 2023Recent methods with deep neural networks for text steganalysis have succeeded in mining various feature representations. However, a limited number of studies have explicitly analyzed potential security issues of generative text steganography. Furthermore,
Wanli Peng +3 more
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Lightweight and Effective Deep Image Steganalysis Network
IEEE Signal Processing Letters, 2022In this letter, a lightweight and effective deep steganalysis network (DSN) with less than 400,000 parameters, called LWENet, is proposed, which focuses on increasing the performance as well as significantly reducing the number of parameters (NP) from ...
S. Weng +3 more
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The impact of information fusion in steganalysis on the example of audio steganalysis
SPIE Proceedings, 2009Information fusion tries to determine the best set of experts in a given problem domain and devise an appropriate function that can optimally combine the decisions of the individual experts. Only few systematic approaches to information fusion exist so far in the signal processing field of steganalysis.
Kraetzer C., Dittmann J.
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