Secure Information Hiding System in Image Steganography

2019 ◽  
Vol 8 (7) ◽  
pp. 226-230
Author(s):  
Zo Nun Khuma ◽  
Dr. Khaing Myat Mon ◽  
Dr. Cho Cho Myint
Keyword(s):  
Information Hiding ◽  
Image Steganography ◽  
Secure Information

Secure information hiding using LSB features in an image

2021 ◽  
Author(s):  
K. Praghash ◽  
Ch. Vidyadhari ◽  
G. NirmalaPriya ◽  
Rajan Cristin
Keyword(s):  
Information Hiding ◽  
Secure Information

scholarly journals Knight Tour for Image Steganography Technique

2019 ◽  
Vol 9 (1) ◽  
pp. 1610-1613
Keyword(s):  
Growth Rate ◽  
Data Hiding ◽  
Information Hiding ◽  
High Capacity ◽  
Image Steganography ◽  
Cover Image ◽  
The Internet ◽  
Sensitive Information ◽  
Image File ◽  
Ascii Code

The growth rate of the Internet is exceeding that of any previous technology. As the Internet has become the major medium for transferring sensitive information, the security of the transferred message has now become the utmost priority. To ensure the security of the transmitted data, Image steganography has emerged out as an eminent tool of information hiding. The frequency of availability of image file is high and provides high capacity. In this paper, a method of secure data hiding in image is proposed that uses knight tour positions and further 8-queen positions in 8*8 pixel blocks.The cover image is divided into 8*8 pixel blocks and pixels are selected from each block corresponding to the positions of Knight in 8*8 chessboard starting from different pixel positions. 8-pixel values are selected from alternate knight position. Selected pixels values converted to 8-bit ASCII code and result in 8* 8 bit matrix. 8-Queen’s solution on 8*8 chessboard is applied on 8*8 bit matrix. The bits selected from 8-Queens positions and compared with 8-bit ASCII code of message characters. The proposed algorithm changes the LSB of only some of the pixels based on the above comparison. Based on parameters like PSNR and MSE the efficiency of the method is checked after implementation. Then the comparison done with some already proposed techniques. This is how, image steganography showed interesting and promising results when compared with other techniques.

Secure Information Delivery through High Bitrate Data Embedding within Digital Video and its Application to Audio/Video Synchronization

2012 ◽  
Vol 6 (4) ◽  
pp. 71-93
Author(s):  
Ming Yang ◽  
Chih-Cheng Hung ◽  
Edward Jung
Keyword(s):  
Video Compression ◽  
Information Hiding ◽  
Secure Communication ◽  
Digital Video ◽  
Lossy Compression ◽  
Data Encryption ◽  
Practical Applications ◽  
Secure Information ◽  
Video Synchronization ◽  
Audio Video

Secure communication has traditionally been ensured with data encryption, which has become easier to break than before due to the advancement of computing power. For this reason, information hiding techniques have emerged as an alternative to achieve secure communication. In this research, a novel information hiding methodology is proposed to deliver secure information with the transmission/broadcasting of digital video. Secure data will be embedded within the video frames through vector quantization. At the receiver end, the embedded information can be extracted without the presence of the original video contents. In this system, the major performance goals include visual transparency, high bitrate, and robustness to lossy compression. Based on the proposed methodology, the authors have developed a novel synchronization scheme, which ensures audio/video synchronization through speech-in-video techniques. Compared to existing algorithms, the main contributions of the proposed methodology are: (1) it achieves both high bitrate and robustness against lossy compression; (2) it has investigated impact of embedded information to the performance of video compression, which has not been addressed in previous research. The proposed algorithm is very useful in practical applications such as secure communication, captioning, speech-in-video, video-in-video, etc.

scholarly journals Coverless image steganography based on DenseNet feature mapping

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Qiang Liu ◽  
Xuyu Xiang ◽  
Jiaohua Qin ◽  
Yun Tan ◽  
Yao Qiu
Keyword(s):  
Information Hiding ◽  
Binary Tree ◽  
State Of The Art ◽  
Image Steganography ◽  
High Dimensional ◽  
Feature Mapping ◽  
Hidden Information ◽  
Geometric Attacks ◽  
Coverless Information Hiding ◽  
Cis Methods

Abstract Since the concept of coverless information hiding was proposed, it has been greatly developed due to its effectiveness of resisting the steganographic tools. Most existing coverless image steganography (CIS) methods achieve excellent robustness under non-geometric attacks. However, they do not perform well under some geometric attacks. Towards this goal, a CIS algorithm based on DenseNet feature mapping is proposed. Deep learning is introduced to extract high-dimensional CNN features which are mapped into hash sequences. For the sender, a binary tree hash index is built to accelerate index speed of searching hidden information and DenseNet hash sequence, and then, all matched images are sent. For the receiver, the secret information can be recovered successfully by calculating the DenseNet hash sequence of the cover image. During the whole steganography process, the cover images remain unchanged. Experimental results and analysis show that the proposed scheme has better robust compared with the state-of-the-art methods under geometric attacks.

Secure information hiding based on computationally intractable problems

2003 ◽  
Vol 6 (1) ◽  
pp. 21-33
Author(s):  
S. Armeni ◽  
D. Christodulakis ◽  
I. Kostopoulos ◽  
Y. C. Stamatiou ◽  
M. Xenos
Keyword(s):  
Information Hiding ◽  
Secure Information ◽  
Intractable Problems

scholarly journals The Embedding Performance of StegSVM Model in Image Steganography

2018 ◽  
Vol 12 (1) ◽  
pp. 233
Author(s):  
Hanizan Shaker Hussain ◽  
Roshidi Din ◽  
Mohd Hanif Ali ◽  
Nor Balqis
Keyword(s):  
Human Visual System ◽  
Information Hiding ◽  
Image Steganography ◽  
The Other ◽  
Image Domain ◽  
Embedding Technique ◽  
Expected Performance ◽  
Technique Evaluation ◽  
Embedding Performance ◽  
Intelligent Methods

This paper focuses on one of the areas of information hiding which is image steganography. It proposes the StegSVM model as an embedding technique in steganography that has exploited human visual system through Shifted LSB that shows an expected performance. The performance of this technique evaluation is based on imperceptibility and robustness of the technique compared to the other previous models in image steganography doamin. Thus, the result shows that the proposed StegSVM model is promising. For further work, it is suggested that the other image domain through other intelligent methods should be investigated.

scholarly journals A New Method of Image Steganography Using 7th Bit of a Pixel as Indicator by Introducing the Successive Temporary Pixel in the Gray Scale Image

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Kamaldeep Joshi ◽  
Swati Gill ◽  
Rajkumar Yadav
Keyword(s):  
Image Coding ◽  
Information Hiding ◽  
High Capacity ◽  
Image Steganography ◽  
New Method ◽  
The Internet ◽  
Mathematical Function ◽  
Sensitive Information ◽  
Gray Scale ◽  
Gray Scale Image

As the internet has become the medium for transferring the sensitive information, the security of the transferred message has become the utmost priority. Image steganography has emerged out as the eminent tool of information hiding that ensures the security of the transmitted data. Image files provide high capacity, and their frequency of availability over the internet is also high. In this paper, a method of image coding is proposed that hides the information along a selected pixel and on the next value of the selected pixel, that is, pixel + 1. One bit is hidden at the selected pixel, and the second bit is hidden on the pixel +1 value. On the basis of the 7th bit of the pixels of an image, a mathematical function is applied at the 7th bit of the pixels, which generates a temporary variable (pixel + 1). The 7th bit of the selected pixel and 7th bit of pixel + 1 are used for information hiding and extraction. On the basis of a combination of these two values, two bits of the message can be hidden on each pixel. After implementation, the efficiency of the method is checked on the basis of parameters like PSNR and MSE, and then comparison with some already proposed techniques was done. This proposed image steganography showed interesting, promising results when compared with other existing techniques.

Introduction to Image Steganography and Steganalysis

2013 ◽  
pp. 209-237
Author(s):  
Michiharu Niimi ◽  
Hideki Noda
Keyword(s):  
Image Segmentation ◽  
Data Structures ◽  
Information Hiding ◽  
Image Data ◽  
Complexity Measure ◽  
Image Steganography ◽  
The Internet ◽  
Reversible Information Hiding ◽  
Bit Plane ◽  
Steganalysis Method

This chapter reviews information hiding methods, with a focus on steganography and steganalysis. First, the authors summarize image data structures and image formats required by computers and the Internet. They then introduce several information hiding methods based on image formats including lossless (non-compression based), limited color-based image data, JPEG, and JPEG2000. The authors describe a steganographic method in detail, which is based on image segmentation using a complexity measure. They also introduce a method for applying this to palette-based image formats, reversible information hiding for grayscale images, and JPEG2000 steganography. The steganographic methods for JPEG and JPEG2000 described in this chapter give particular consideration to the naturalness of cover data. In the steganalysis section, the authors introduce two methods, i.e., a specific steganalysis method for LSB steganography and Bit-Plane Complexity Segmentation (BPCS) stegnography.

Adaptive Image Steganography Based on Structural Similarity Metric

2011 ◽  
pp. 454-471 ◽  
Author(s):  
Guangjie Liu ◽  
Shiguo Lian ◽  
Yuewei Dai ◽  
Zhiquan Wang
Keyword(s):  
Dynamic Programming ◽  
Information Hiding ◽  
Structural Similarity ◽  
Image Steganography ◽  
The Other ◽  
Trade Off ◽  
Similarity Metric ◽  
Adaptive Quantization ◽  
The Future ◽  
Distortion Index

Image steganography is a common form of information hiding which embeds as many message bits into images and keep the introduced distortion imperceptible. How to balance the trade-off between the capacity and imperceptibility has become a very important issue in the researches of steganography. In this chapter, we discuss one kind of the solution for disposing the trade-off, named adaptive image steganography. After a brief review, we present two methods based on structural similarity metric. The first one is based on the generalized LSB, in which the substitution depth vector is obtained via the dynamic programming under the constraint of an allowable distortion. The second method is proposed to use adaptive quantization-embedder to carry message bits. Different from the first method, the distortion index is constructed by contrast-correlation distortion. The other difference is that the parameters of the adaptive quantization embedder are embedded into the image containing message bits by the reversible da a hiding method. Beside that, we also bring forward some attractive directions worthy of being studied in the future. Furthermore, we find that the existing methods do not have a good way to control the amount of information and the distortion as an extract manner, and most schemes are designed just according to the experiences and experiments.

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