Results 181 to 190 of about 6,282 (220)

Steganalysis on Digital Watermarking: Is Your Defense Truly Impervious?

arXiv.org
Digital watermarking techniques are crucial for copyright protection and source identification of images, especially in the era of generative AI models.
Pei Yang, Hai Ci, Yiren Song, Mike Zheng Shou   +3 more
semanticscholar   +1 more source

Steganalysis Feature Selection With Multidimensional Evaluation and Dynamic Threshold Allocation

IEEE transactions on circuits and systems for video technology (Print)
Steganalysis feature selection shows excellent effectiveness on elevating the detection efficiency and decreasing time-space cost. However, the single evaluation criterion for features and the subjective selection basis always lead to valuable features ...
Yuanyuan Ma, Lige Xu, Yi Zhang, Tao Zhang, X. Luo   +4 more
semanticscholar   +1 more source

Towards Next-Generation Steganalysis: LLMs Unleash the Power of Detecting Steganography

arXiv.org
Linguistic steganography provides convenient implementation to hide messages, particularly with the emergence of AI generation technology. The potential abuse of this technology raises security concerns within societies, calling for powerful linguistic ...
Minhao Bai, Jinshuai Yang, Kaiyi Pang, Huili Wang, Yongfeng Huang   +4 more
semanticscholar   +1 more source

FedSteg: A Federated Transfer Learning Framework for Secure Image Steganalysis

IEEE Transactions on Network Science and Engineering, 2020
The protection of user private data has long been the focus of AI security. We know that training machine learning models rely on large amounts of user data. However, user data often exists in the form of isolated islands that can not be integrated under
Hongwei Yang, Hui He, Weizhe Zhang, Xiaochun Cao   +3 more
semanticscholar   +1 more source

Double Embedding Steganalysis

Proceedings of the 2nd International Workshop on Multimedia Privacy and Security, 2018
The rise of social networks during the last 10 years has created a situation in which up to 100 million new images and photographs are uploaded and shared by users every day. This environment poses a ideal background for those who wish to communicate covertly by the use of steganography.
Martin Steinebach, Andre Ester, Huajian Liu, Sascha Zmuzinksi   +3 more
openaire   +1 more source

An Ensemble of Classifiers Approach to Steganalysis

2010 20th International Conference on Pattern Recognition, 2010
Most work on steganalysis, except a few exceptions, have primarily focused on providing features with high discrimination power without giving due consideration to issues concerning practical deployment of steganalysis methods. In this work, we focus on machine learning aspect of steganalyzer design and utilize a hierarchical ensemble of classifiers ...
Sevinc Bayram, Ahmet Emir Dirik, Husrev T. Sencar, Nasir D. Memon   +3 more
openaire   +3 more sources

Textural Features for Steganalysis

2013
It is observed that the co-occurrence matrix, one kind of textural features proposed by Haralick et al., has played a very critical role in steganalysis. On the other hand, the data hidden in the image texture area has been known difficult to detect for years, and the modern steganographic schemes tend to embed data into complicated texture area where ...
Yun Q. Shi 0001, Patchara Sutthiwan, Licong Chen   +2 more
openaire   +1 more source

Steganalysis of facsimile

The 7th International Conference on Advanced Communication Technology, 2005, ICACT 2005., 2005
Communications associated with illicit activity has become a new focus of advanced communication technology. A steganographic method of binary image, which embeds data in facsimile by modifying the runlength of black pixel can build a covert communication over fax.
null Yunbiao Guo, null Xingang You, null Chuntian Zhang, null Lan Hu, null Linna Zhou   +4 more
openaire   +1 more source

Adaptive Image Steganalysis

Multimedia Tools and Applications, 2017
Image steganography is the process of sending messages secretly by hiding the message in AN image content. Although steganography hides information in any kinds of digital mediums, digital images are the most popular carrier because of the frequency of usage in the internet.
openaire   +1 more source

Selection of Rich Model Steganalysis Features Based on Decision Rough Set $\alpha$ -Positive Region Reduction

IEEE transactions on circuits and systems for video technology (Print), 2019
Steganography detection based on Rich Model features is a hot research direction in steganalysis. However, rich model features usually result a large computation cost.
Yuanyuan Ma, Xiangyang Luo, Xiaolong Li, Z. Bao, Yi Zhang   +4 more
semanticscholar   +1 more source