Steganography attack based on Discrete Spring Transform and image geometrization

Qi, Qilin; Sharp, Aaron; Yang, Yaoqing; Peng, Dongming; Sharif, Hamid

doi:10.1109/iwcmc.2014.6906416

Cited by 4 publications

(3 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These techniques were able to maintain an acceptable audio quality. Another method which will effectively remove the steganographic information in spatial and frequency domain for image, video and audio was introduced by Sharp, A., et al [22][23][24]. Authors proposed an attack using discrete spring transform which will only distort the numerical value of the carrier media while keeping visual quality in a high level.…”

Section: Related Workmentioning

confidence: 99%

Anti-forensic Approach to Remove StegoContent from Images and Videos

Amritha

Sethumadhavan

Ramakrishnan

et al. 2019

JCSM

View full text Add to dashboard Cite

Covert transmission of information hidden in different media to either a general or targeted audience constitutes steganography. However, this technique can be misused to transmit undesirable information. Traditionally the removal of such content necessitated the knowledge of the steganographic algorithm used. However, we address the scenario where such stego is removed using generic image processing operations along with an anti forensic method without assuming any knowledge of the steganographic algorithm used. The application of generic image processing operations also causes degradation of cover image, which can also be restored using this anti forensic method. Our procedure has been tested on a variety of steganographic algorithms including HUGO-BD, WOW, Synch and J-UNIWARD. By applying universal steganalysis we found that all images which have been subjected to our procedure have become stego free. However, a direct evaluation of the stego content assuming knowledge of the stego content and its location showed that 80 percentage of the stego is removed without significantly impacting the visual image quality. Video stream containing isolated static images have been addressed in this paper. The peak signal-to-noise ratio and structural

show abstract

Section: Related Workmentioning

confidence: 99%

Anti-forensic Approach to Remove StegoContent from Images and Videos

Amritha

Sethumadhavan

Ramakrishnan

et al. 2019

JCSM

View full text Add to dashboard Cite

show abstract

“…Some of the highly robust steganographies are built based on the existing methods . Those methods match the features of the normal carriers to protect the hidden data to be discovered by the countermeasures.…”

Section: Literature Reviewmentioning

confidence: 99%

Generic attack against robust steganography based on spring transform and geometrization

Sharp

Peng

et al. 2016

Security Comm. Networks

Self Cite

View full text Add to dashboard Cite

There have been many robust image steganography methods that are invented in recent decades. However, this technique also may be used by malicious users to transmit dangerous information through the Internet beyond the control of the security agencies. How to detect and/or block potentially dangerous information transmission on the Internet through billions of images while not affecting the normal digital images becomes a challenging problem. Existing steganalysis methods or steganography attacking methods cannot be used for analyzing a large volume of digital images in a short time. In this paper, we propose an effective steganography attacking method that is not limited by the types of the steganography method. The proposed method can process the digital images to remove the potentially dangerous hidden information while keeping the digital image in a high visual quality. Inspired by the way in which printers and scanners work, our method decouples the human visual perception and the digital image's numerical values. It causes the numerical values of the image to change dramatically, and then the hidden information are largely damaged, while at the same time, the visual image quality can be maintained. Our experimental results have demonstrated that the peak signal‐to‐noise ratio of images can be above 32 dB while the stego data are destroyed. Copyright © 2016 John Wiley & Sons, Ltd.

show abstract

“…DST was first proposed as a way to attack the steganography embedded in the multimedia signal [12][13][14][15][16][17]. The basic idea of DST is to eliminate the perceptual redundancy of the multimedia signal [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

DST approach to enhance audio quality on lost audio packet steganography

Peng

Sharif

2016

EURASIP J. on Info. Security

Self Cite

View full text Add to dashboard Cite

Lost audio packet steganography (LACK) is a steganography technique established on the VoIP network. LACK provides a high-capacity covert channel over VoIP network by artificially delaying and dropping a number of packets in use to convey stegnogram. However, the increasing loss of packets will hurt the quality of the VoIP service. The quality deterioration will not only affect the legitimate VoIP service but also constrain the capacity of the covert channel. Discrete spring transform (DST) is proven to be a way to eliminate the perceptual redundancy in the multimedia signal. In this paper, the DST is applied on the LACK so that the perceptual redundancy of the voice frames is suppressed. In this way, the less redundant VoIP frames with perceptual equivalent quality can be transmitted in a channel whose capacity is squeezed by the established covert channel. As a result, the VoIP perceptual quality can be maintained with the existence of the covert channel. Meanwhile, the proposed DSTbased method demonstrates the possibilities in exploiting the perceptual space of the multimedia signal. The simulation results show that the DST on LACK achieves up to 24 % more capacity over the LACK scheme.

show abstract

Steganography attack based on Discrete Spring Transform and image geometrization

Cited by 4 publications

References 17 publications

Anti-forensic Approach to Remove StegoContent from Images and Videos

Anti-forensic Approach to Remove StegoContent from Images and Videos

Generic attack against robust steganography based on spring transform and geometrization

DST approach to enhance audio quality on lost audio packet steganography

Contact Info

Product

Resources

About