An Advanced Least-Significant-Bit Embedding Scheme for Steganographic Encoding

Lee, Yeuan-Kuen; Bell, Graeme; Huang, Shih‐Yu; Wang, Ran-Zan; Shyu, Shyong-Jian

doi:10.1007/978-3-540-92957-4_31

Cited by 19 publications

(10 citation statements)

References 7 publications

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“…Nevertheless; this only reduces the chance of the encrypted image being detected to enhance the security level of the encrypted images. Moreover; a another system proposed using advanced LSB embedding scheme which breaks the regular pattern of PoVs in the histogram domain, increasing the difficulty of steganalysis and thereby raising the level of security [13]. However, the increasing amount of data embedded in the image is not a consideration in this research.…”

Section: Literature Reviewmentioning

confidence: 99%

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ILSB: Indexing with Least Significant Bit Algorithm for Effective Data Hiding

Senarathne¹,

Zoysa²

2017

IJCA

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Data transmission is frequently face intrusions issues. Different data hiding methods are there to address this problem. Steganography being one; intends on writing hidden messages in such a way that no one, apart from the sender and intended recipient, suspects the existence of the message. Moreover, cryptography is a tool used in protecting information using cipher text. However, these methods are subjected to suspicion and prone to visual and statistical attacks. While trying to overcome such problems, researchers need to compromise with imperceptibility and hiding capacity. Any basic algorithms including traditional Least Significant Bit algorithm are simpler and faster processing although they are highly vulnerable to these visual and statistical attacks. Once the algorithm is known extracting the hidden information is fairly simple using steganalysis tools. Thus, these are having relatively low data hiding capacity, security compared to the algorithms with enhancements. These enhancements use complex mathematical functions with existing algorithms using cryptography as a method of improving security. The employing cryptography involves complex mathematical calculations requiring advanced processing capabilities leading to slow performance. As a result; it's difficult to work in low processing environments.This research focuses on developing a system that adapts to the enhanced security without using complex mathematical functions with ways in which to improve data hiding capacity. Having less complexity intern provides the user with lower processing environment. The system uses an indexing technique in hiding data inside the cover image providing high security. The proposed system will have an additional step residing outside the traditional Least Significant Bit algorithm which provides hiding data with less vulnerability to intrusion. The requirement of an indexing image will provide the user with high security because the extraction process will totally depend on the bit patterns of the indexing image. This enhancement will be an attempt to overcome threats and weaknesses in the traditional Least Significant Bit algorithm and enhance the security of data hiding.

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Section: Literature Reviewmentioning

confidence: 99%

“…Secondly, from a PSNR point of view, the fidelity of the stego images resulting from the proposed scheme is as good as those created by traditional LSB embedding. Finally, and most importantly, the PoVs artifact is removed from the stego-images [13].…”

Section: Advanced Lsb Through Breaks the Regular Pattern Of Povs In Tmentioning

confidence: 99%

ILSB: Indexing with Least Significant Bit Algorithm for Effective Data Hiding

Senarathne¹,

Zoysa²

2017

IJCA

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“…The idea relies on inserting a unique modification or signature not visible to the human eye. This allows to prove legitimate ownership by presenting that the owner's unique signature is embedded into the digital media [7], [8].…”

Section: A Watermarkingmentioning

confidence: 99%

Stealing Knowledge from Protected Deep Neural Networks Using Composite Unlabeled Data

Mosafi¹,

David²,

Netanyahu³

2019

2019 International Joint Conference on Neural Networks (IJCNN)

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As state-of-the-art deep neural networks are deployed at the core of more advanced AI-based products and services, the incentive for copying them (i.e., their intellectual properties) by rival adversaries is expected to increase considerably over time. The best way to extract or steal knowledge from such networks is by querying them using a large dataset of random samples and recording their output, followed by training a student network to mimic these outputs, without making any assumption about the original networks. The most effective way to protect against such a mimicking attack is to provide only the classification result, without confidence values associated with the softmax layer.In this paper, we present a novel method for generating composite images for attacking a mentor neural network using a student model. Our method assumes no information regarding the mentor's training dataset, architecture, or weights. Further assuming no information regarding the mentor's softmax output values, our method successfully mimics the given neural network and steals all of its knowledge. We also demonstrate that our student network (which copies the mentor) is impervious to watermarking protection methods, and thus would not be detected as a stolen model.Our results imply, essentially, that all current neural networks are vulnerable to mimicking attacks, even if they do not divulge anything but the most basic required output, and that the student model which mimics them cannot be easily detected and singled out as a stolen copy using currently available techniques.

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“…No extra data is required, like the original picture, and still makes sure that embedding and retrieval are done with the same pixels [5].…”

Section: Filterfirstmentioning

confidence: 99%

Hidden Data Transmission using Image Steganography

Mistry¹,

Desai²,

Jagad³

2015

IJCA

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Steganography can be defined as the science of hiding data behind images in such a way that no one except the sender and receiver has any idea about the transfer of hidden message taking place. In this paper, light is thrown on the algorithm using LSB of the image pixels to store data and transfer in a hidden manner, such that it won't attract attention and the observers will be unaware of any data transmission taking place. The project involved implement and compare three algorithms and evaluate the results to find the most efficient algorithm.

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An Advanced Least-Significant-Bit Embedding Scheme for Steganographic Encoding

Cited by 19 publications

References 7 publications

ILSB: Indexing with Least Significant Bit Algorithm for Effective Data Hiding

ILSB: Indexing with Least Significant Bit Algorithm for Effective Data Hiding

Stealing Knowledge from Protected Deep Neural Networks Using Composite Unlabeled Data

Hidden Data Transmission using Image Steganography

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