Steganography is the art and science of covert communication. The secret information can be concealed in content such as image, audio, or video. This paper provides a novel image steganography technique to hide both image and key in color cover image using Discrete Wavelet Transform (DWT) and Integer Wavelet Transform (IWT). There is no visual difference between the stego image and the cover image. The extracted image is also similar to the secret image. This is proved by the high PSNR (Peak Signal to Noise Ratio), value for both stego and extracted secret image. The results are compared with the results of similar techniques and it is found that the proposed technique is simple and gives better PSNR values than others.
A NOVEL IMAGE STEGANOGRAPHY APPROACH USING MULTI-LAYERS DCT FEATURES BASED ON...ijma
Steganography is the science of hidden data in the cover image without any updating of the cover image.
The recent research of the steganography is significantly used to hide large amount of information within
an image and/or audio files. This paper proposed a new novel approach for hiding the data of secret image
using Discrete Cosine Transform (DCT) features based on linear Support Vector Machine (SVM)
classifier. The DCT features are used to decrease the image redundant information. Moreover, DCT is
used to embed the secrete message based on the least significant bits of the RGB. Each bit in the cover
image is changed only to the extent that is not seen by the eyes of human. The SVM used as a classifier to
speed up the hiding process via the DCT features. The proposed method is implemented and the results
show significant improvements. In addition, the performance analysis is calculated based on the
parameters MSE, PSNR, NC, processing time, capacity, and robustness.
Image Encryption Based on Pixel Permutation and Text Based Pixel Substitutionijsrd.com
Digital image Encryption techniques play a very important role to prevent image from unauthorized access. There are many types of methods available that can do Image Encryption, and the majority of them are scrambling algorithms based on pixel shuffling, which cannot change the histogram of an image. Hence, their security performances are not good. The encryption method that combines the pixel exchanging and gray level changing can handles reach a good chaotic effect. In this paper we focus on an image encryption technique based on pixel wise shuffling with the help of skew tent map and text based pixel substitution. The PSNR, NPCR and CC obtained by our technique shows that the proposed technique gives better result than the existing techniques.
A NOVEL IMAGE STEGANOGRAPHY APPROACH USING MULTI-LAYERS DCT FEATURES BASED ON...ijma
Steganography is the science of hidden data in the cover image without any updating of the cover image.
The recent research of the steganography is significantly used to hide large amount of information within
an image and/or audio files. This paper proposed a new novel approach for hiding the data of secret image
using Discrete Cosine Transform (DCT) features based on linear Support Vector Machine (SVM)
classifier. The DCT features are used to decrease the image redundant information. Moreover, DCT is
used to embed the secrete message based on the least significant bits of the RGB. Each bit in the cover
image is changed only to the extent that is not seen by the eyes of human. The SVM used as a classifier to
speed up the hiding process via the DCT features. The proposed method is implemented and the results
show significant improvements. In addition, the performance analysis is calculated based on the
parameters MSE, PSNR, NC, processing time, capacity, and robustness.
Image Encryption Based on Pixel Permutation and Text Based Pixel Substitutionijsrd.com
Digital image Encryption techniques play a very important role to prevent image from unauthorized access. There are many types of methods available that can do Image Encryption, and the majority of them are scrambling algorithms based on pixel shuffling, which cannot change the histogram of an image. Hence, their security performances are not good. The encryption method that combines the pixel exchanging and gray level changing can handles reach a good chaotic effect. In this paper we focus on an image encryption technique based on pixel wise shuffling with the help of skew tent map and text based pixel substitution. The PSNR, NPCR and CC obtained by our technique shows that the proposed technique gives better result than the existing techniques.
TEXT STEGANOGRAPHY USING LSB INSERTION METHOD ALONG WITH CHAOS THEORYIJCSEA Journal
The art of information hiding has been around nearly as long as the need for covert communication. Steganography, the concealing of information, arose early on as an extremely useful method for covert information transmission. Steganography is the art of hiding secret message within a larger image or message such that the hidden message or an image is undetectable; this is in contrast to cryptography, where the existence of the message itself is not disguised, but the content is obscure. The goal of a steganographic method is to minimize the visually apparent and statistical differences between the cover data and a steganogram while maximizing the size of the payload. Current digital image steganography presents the challenge of hiding message in a digital image in a way that is robust to image manipulation and attack. This paper explains about how a secret message can be hidden into an image using least significant bit insertion method along with chaos.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
A NEW ALGORITHM FOR DATA HIDING USING OPAP AND MULTIPLE KEYSEditor IJMTER
Steganography gained significance in the past few years due to the increasing need
for providing secrecy in an open environment like the internet. With almost anyone can
observe the communicated data all around, steganography attempts to hide the very existence
of the message and make communication undetectable. In this paper we propose a modern
technique with Integer Wavelet transform (IWT) and double key to accomplish high hiding
capability, high security and good visual quality. Here cover image is transformed in to
wavelet transform co-efficients and the coefficients are selected randomly by using Key-2 for
embedding the data. Key-1 is used to calculate the number of bits to be embedded in the
randomly selected coefficients. Finally the Optimum Pixel Adjustment Process(OPAP) is
applied to the stego image to reduce the data embedding error.
Steganography is going to gain its importance due to the exponential growth and secret communication of potential computer users over the internet [5]. It can also be defined as the study of invisible communication that usually deals with the ways of hiding the existence of the communicated message. Generally data embedding is achieved in communication, image, text, voice or multimedia content for copyright, military communication, authentication and many other purposes [2]. In image Steganography, secret communication is achieved to embed a message into cover image (used as the carrier to embed message into) and generate a stego- image (generated image which is carrying a hidden message)[1]. In this paper we have critically analyzed various steganographic techniques and also have covered steganography overview its major types, classification, applications [3]. KEYWORDS: STEGANOGRAPHY, STEGO IMAGE, COVER IMAGE, LSB
Implementation of Image Steganography Using 2-Level DWT Technique .............................................1
Aayushi Verma, Rajshree Nolkha, Aishwarya Singh and Garima Jaiswal
Efficient Neighbor Routing in Wireless Mesh Networks.......................................................................1
V. Lakshmi Praba and A. Mercy Rani
Content Based Messaging Model for Library Information System........................................................1
Surbhi Agarwal, Chandrika Chanda and Senthil Murugan B.
Building an Internal Cloud for IT Support Organisations: A Preview .....................................................1
S. M. M. M Kalyan Kumar and Dr S. C. Pradhan
Use of Intelligent Business, a Method for Complete Fulfillment of E-government ................................1
M. Nili Ahmadabadi, Masoud Najafi and Peyman Gholami
Comparison of Swarm Intelligence Techniques ...................................................................................1
Prof. S. A. Thakare
An Efficient Rough Set Approach in Querying Covering Based Relational Databases.............................1
P. Prabhavathy and Dr. B. K. Tripathy
Robust Watermarking Technique using 2D Logistic Map and Elliptic Curve Crypto...idescitation
Copyright protection is a vital issue in modern day’s data transmission over
internet. For copyright protection, watermarking technique is extensively used. In this
paper, we have proposed a robust watermarking scheme using 2D Logistic map and elliptic
curve cryptosystem (ECC) in the DWT domain. The combined encryption has been taken to
enhance the security of the watermark before the embedding phase. The PSNR value shows
the difference between original cover and embedded cover is minimal. Similarly, NC values
show the robustness and resistance capability of the proposed technique from the common
attacks such as scaling, Gaussian noise etc. Thus, this combined version of 2D Logistic map
and Elliptic curve cryptosystem can be used in case of higher security requirement of the
watermark signal.
Data Steganography for Optical Color Image CryptosystemsCSCJournals
In this paper, an optical color image cryptosystem with a data hiding scheme is proposed. In the proposed optical cryptosystem, a confidential color image is embedded into the host image of the same size. Then the stego-image is encrypted by using the double random phase encoding algorithm. The seeds to generate random phase data are hidden in the encrypted stego-image by a content-dependent and low distortion data embedding technique. The confidential image and secret data delivery is accomplished by hiding the image into the host image and embedding the data into the encrypted stego-image. Experimental results show that the proposed data steganographic cryptosystem provides large data hiding capacity and high reconstructed image quality.
Image fusion is a sub field of image processing in which more than one images are fused to create an image where all the objects are in focus. The process of image fusion is performed for multi-sensor and multi-focus images of the same scene. Multi-sensor images of the same scene are captured by different sensors whereas multi-focus images are captured by the same sensor. In multi-focus images, the objects in the scene which are closer to the camera are in focus and the farther objects get blurred. Contrary to it, when the farther objects are focused then closer objects get blurred in the image. To achieve an image where all the objects are in focus, the process of images fusion is performed either in spatial domain or in transformed domain. In recent times, the applications of image processing have grown immensely. Usually due to limited depth of field of optical lenses especially with greater focal length, it becomes impossible to obtain an image where all the objects are in focus. Thus, it plays an important role to perform other tasks of image processing such as image segmentation, edge detection, stereo matching and image enhancement. Hence, a novel feature-level multi-focus image fusion technique has been proposed which fuses multi-focus images. Thus, the results of extensive experimentation performed to highlight the efficiency and utility of the proposed technique is presented. The proposed work further explores comparison between fuzzy based image fusion and neuro fuzzy fusion technique along with quality evaluation indices.
Image Steganography Using HBC and RDH TechniqueEditor IJCATR
There are algorithms in existence for hiding data within an image. The proposed scheme treats the image as a whole. Here
Integer Cosine Transform (ICT) and Integer Wavelet Transform (IWT) is combined for converting signal to frequency. Hide Behind
Corner (HBC) algorithm is used to place a key at corners of the image. All the corner keys are encrypted by generating Pseudo
Random Numbers. The Secret keys are used for corner parts. Then the hidden image is transmitted. The receiver should be aware of
the keys that are used at the corners while encrypting the image. Reverse Data Hiding (RDH) is used to get the original image and it
proceeds once when all the corners are unlocked with proper secret keys. With these methods the performance of the stegnographic
technique is improved in terms of PSNR value.
Novel DCT based watermarking scheme for digital imagesIDES Editor
There is an ever growing interest in copyright
protection of multimedia content, thus digital
watermarking techniques are widely practiced. Due to
the internet connectivity and digital libraries the
research interest of protecting digital content
watermarking is extensively researched. In this paper
we present a novel watermark generation scheme
based on the histogram of the image and apply it to the
original image in the transform(DCT) domain. Further
we study the performance of the watermark against
some common attacks that can take place with images.
Experimental results show that the embedded
watermark is imperceptible and image quality is not
degraded.
A SECURE COLOR IMAGE STEGANOGRAPHY IN TRANSFORM DOMAINijcisjournal
Steganography is the art and science of covert communication. The secret information can be concealed in content such as image, audio, or video. This paper provides a novel image steganography technique to hide both image and key in color cover image using Discrete Wavelet Transform (DWT) and Integer Wavelet Transform (IWT). There is no visual difference between the stego image and the cover image. The extracted image is also similar to the secret image. This is proved by the high PSNR (Peak Signal to Noise Ratio), value for both stego and extracted secret image. The results are compared with the results of similar techniques and it is found that the proposed technique is simple and gives better PSNR values than others.
A SECURE COLOR IMAGE STEGANOGRAPHY IN TRANSFORM DOMAINijcisjournal
Steganography is the art and science of covert communication. The secret information can be concealed in content such as image, audio, or video. This paper provides a novel image steganography technique to hide both image and key in color cover image using Discrete Wavelet Transform (DWT) and Integer Wavelet Transform (IWT). There is no visual difference between the stego image and the cover image. The extracted image is also similar to the secret image. This is proved by the high PSNR (Peak Signal to Noise Ratio), value for both stego and extracted secret image. The results are compared with the results of similar techniques and it is found that the proposed technique is simple and gives better PSNR values than others.
Steganography is a best method for in secret communicating information during the transference of data. Images are an appropriate method that used in steganography can be used to protection the simple bits and pieces. Several systems, this one as color scale images steganography and grayscale images steganography, are used on color and store data in different techniques. These color images can have very big amounts of secret data, by using three main color modules. The different color modules, such as HSV-(hue, saturation, and value), RGB-(red, green, and blue), YCbCr-(luminance and chrominance), YUV, YIQ, etc. This paper uses unusual module to hide data: an adaptive procedure that can increase security ranks when hiding a top secret binary image in a RGB color image, which we implement the steganography in the YCbCr module space. We performed Exclusive-OR (XOR) procedures between the binary image and the RGB color image in the YCBCR module space. The converted byte stored in the 8-bit LSB is not the actual bytes; relatively, it is obtained by translation to another module space and applies the XOR procedure. This technique is practical to different groups of images. Moreover, we see that the adaptive technique ensures good results as the peak signal to noise ratio (PSNR) and stands for mean square error (MSE) are good. When the technique is compared with our previous works and other existing techniques, it is shown to be the best in both error and message capability. This technique is easy to model and simple to use and provides perfect security with unauthorized.
TEXT STEGANOGRAPHY USING LSB INSERTION METHOD ALONG WITH CHAOS THEORYIJCSEA Journal
The art of information hiding has been around nearly as long as the need for covert communication. Steganography, the concealing of information, arose early on as an extremely useful method for covert information transmission. Steganography is the art of hiding secret message within a larger image or message such that the hidden message or an image is undetectable; this is in contrast to cryptography, where the existence of the message itself is not disguised, but the content is obscure. The goal of a steganographic method is to minimize the visually apparent and statistical differences between the cover data and a steganogram while maximizing the size of the payload. Current digital image steganography presents the challenge of hiding message in a digital image in a way that is robust to image manipulation and attack. This paper explains about how a secret message can be hidden into an image using least significant bit insertion method along with chaos.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
A NEW ALGORITHM FOR DATA HIDING USING OPAP AND MULTIPLE KEYSEditor IJMTER
Steganography gained significance in the past few years due to the increasing need
for providing secrecy in an open environment like the internet. With almost anyone can
observe the communicated data all around, steganography attempts to hide the very existence
of the message and make communication undetectable. In this paper we propose a modern
technique with Integer Wavelet transform (IWT) and double key to accomplish high hiding
capability, high security and good visual quality. Here cover image is transformed in to
wavelet transform co-efficients and the coefficients are selected randomly by using Key-2 for
embedding the data. Key-1 is used to calculate the number of bits to be embedded in the
randomly selected coefficients. Finally the Optimum Pixel Adjustment Process(OPAP) is
applied to the stego image to reduce the data embedding error.
Steganography is going to gain its importance due to the exponential growth and secret communication of potential computer users over the internet [5]. It can also be defined as the study of invisible communication that usually deals with the ways of hiding the existence of the communicated message. Generally data embedding is achieved in communication, image, text, voice or multimedia content for copyright, military communication, authentication and many other purposes [2]. In image Steganography, secret communication is achieved to embed a message into cover image (used as the carrier to embed message into) and generate a stego- image (generated image which is carrying a hidden message)[1]. In this paper we have critically analyzed various steganographic techniques and also have covered steganography overview its major types, classification, applications [3]. KEYWORDS: STEGANOGRAPHY, STEGO IMAGE, COVER IMAGE, LSB
Implementation of Image Steganography Using 2-Level DWT Technique .............................................1
Aayushi Verma, Rajshree Nolkha, Aishwarya Singh and Garima Jaiswal
Efficient Neighbor Routing in Wireless Mesh Networks.......................................................................1
V. Lakshmi Praba and A. Mercy Rani
Content Based Messaging Model for Library Information System........................................................1
Surbhi Agarwal, Chandrika Chanda and Senthil Murugan B.
Building an Internal Cloud for IT Support Organisations: A Preview .....................................................1
S. M. M. M Kalyan Kumar and Dr S. C. Pradhan
Use of Intelligent Business, a Method for Complete Fulfillment of E-government ................................1
M. Nili Ahmadabadi, Masoud Najafi and Peyman Gholami
Comparison of Swarm Intelligence Techniques ...................................................................................1
Prof. S. A. Thakare
An Efficient Rough Set Approach in Querying Covering Based Relational Databases.............................1
P. Prabhavathy and Dr. B. K. Tripathy
Robust Watermarking Technique using 2D Logistic Map and Elliptic Curve Crypto...idescitation
Copyright protection is a vital issue in modern day’s data transmission over
internet. For copyright protection, watermarking technique is extensively used. In this
paper, we have proposed a robust watermarking scheme using 2D Logistic map and elliptic
curve cryptosystem (ECC) in the DWT domain. The combined encryption has been taken to
enhance the security of the watermark before the embedding phase. The PSNR value shows
the difference between original cover and embedded cover is minimal. Similarly, NC values
show the robustness and resistance capability of the proposed technique from the common
attacks such as scaling, Gaussian noise etc. Thus, this combined version of 2D Logistic map
and Elliptic curve cryptosystem can be used in case of higher security requirement of the
watermark signal.
Data Steganography for Optical Color Image CryptosystemsCSCJournals
In this paper, an optical color image cryptosystem with a data hiding scheme is proposed. In the proposed optical cryptosystem, a confidential color image is embedded into the host image of the same size. Then the stego-image is encrypted by using the double random phase encoding algorithm. The seeds to generate random phase data are hidden in the encrypted stego-image by a content-dependent and low distortion data embedding technique. The confidential image and secret data delivery is accomplished by hiding the image into the host image and embedding the data into the encrypted stego-image. Experimental results show that the proposed data steganographic cryptosystem provides large data hiding capacity and high reconstructed image quality.
Image fusion is a sub field of image processing in which more than one images are fused to create an image where all the objects are in focus. The process of image fusion is performed for multi-sensor and multi-focus images of the same scene. Multi-sensor images of the same scene are captured by different sensors whereas multi-focus images are captured by the same sensor. In multi-focus images, the objects in the scene which are closer to the camera are in focus and the farther objects get blurred. Contrary to it, when the farther objects are focused then closer objects get blurred in the image. To achieve an image where all the objects are in focus, the process of images fusion is performed either in spatial domain or in transformed domain. In recent times, the applications of image processing have grown immensely. Usually due to limited depth of field of optical lenses especially with greater focal length, it becomes impossible to obtain an image where all the objects are in focus. Thus, it plays an important role to perform other tasks of image processing such as image segmentation, edge detection, stereo matching and image enhancement. Hence, a novel feature-level multi-focus image fusion technique has been proposed which fuses multi-focus images. Thus, the results of extensive experimentation performed to highlight the efficiency and utility of the proposed technique is presented. The proposed work further explores comparison between fuzzy based image fusion and neuro fuzzy fusion technique along with quality evaluation indices.
Image Steganography Using HBC and RDH TechniqueEditor IJCATR
There are algorithms in existence for hiding data within an image. The proposed scheme treats the image as a whole. Here
Integer Cosine Transform (ICT) and Integer Wavelet Transform (IWT) is combined for converting signal to frequency. Hide Behind
Corner (HBC) algorithm is used to place a key at corners of the image. All the corner keys are encrypted by generating Pseudo
Random Numbers. The Secret keys are used for corner parts. Then the hidden image is transmitted. The receiver should be aware of
the keys that are used at the corners while encrypting the image. Reverse Data Hiding (RDH) is used to get the original image and it
proceeds once when all the corners are unlocked with proper secret keys. With these methods the performance of the stegnographic
technique is improved in terms of PSNR value.
Novel DCT based watermarking scheme for digital imagesIDES Editor
There is an ever growing interest in copyright
protection of multimedia content, thus digital
watermarking techniques are widely practiced. Due to
the internet connectivity and digital libraries the
research interest of protecting digital content
watermarking is extensively researched. In this paper
we present a novel watermark generation scheme
based on the histogram of the image and apply it to the
original image in the transform(DCT) domain. Further
we study the performance of the watermark against
some common attacks that can take place with images.
Experimental results show that the embedded
watermark is imperceptible and image quality is not
degraded.
A SECURE COLOR IMAGE STEGANOGRAPHY IN TRANSFORM DOMAINijcisjournal
Steganography is the art and science of covert communication. The secret information can be concealed in content such as image, audio, or video. This paper provides a novel image steganography technique to hide both image and key in color cover image using Discrete Wavelet Transform (DWT) and Integer Wavelet Transform (IWT). There is no visual difference between the stego image and the cover image. The extracted image is also similar to the secret image. This is proved by the high PSNR (Peak Signal to Noise Ratio), value for both stego and extracted secret image. The results are compared with the results of similar techniques and it is found that the proposed technique is simple and gives better PSNR values than others.
A SECURE COLOR IMAGE STEGANOGRAPHY IN TRANSFORM DOMAINijcisjournal
Steganography is the art and science of covert communication. The secret information can be concealed in content such as image, audio, or video. This paper provides a novel image steganography technique to hide both image and key in color cover image using Discrete Wavelet Transform (DWT) and Integer Wavelet Transform (IWT). There is no visual difference between the stego image and the cover image. The extracted image is also similar to the secret image. This is proved by the high PSNR (Peak Signal to Noise Ratio), value for both stego and extracted secret image. The results are compared with the results of similar techniques and it is found that the proposed technique is simple and gives better PSNR values than others.
Steganography is a best method for in secret communicating information during the transference of data. Images are an appropriate method that used in steganography can be used to protection the simple bits and pieces. Several systems, this one as color scale images steganography and grayscale images steganography, are used on color and store data in different techniques. These color images can have very big amounts of secret data, by using three main color modules. The different color modules, such as HSV-(hue, saturation, and value), RGB-(red, green, and blue), YCbCr-(luminance and chrominance), YUV, YIQ, etc. This paper uses unusual module to hide data: an adaptive procedure that can increase security ranks when hiding a top secret binary image in a RGB color image, which we implement the steganography in the YCbCr module space. We performed Exclusive-OR (XOR) procedures between the binary image and the RGB color image in the YCBCR module space. The converted byte stored in the 8-bit LSB is not the actual bytes; relatively, it is obtained by translation to another module space and applies the XOR procedure. This technique is practical to different groups of images. Moreover, we see that the adaptive technique ensures good results as the peak signal to noise ratio (PSNR) and stands for mean square error (MSE) are good. When the technique is compared with our previous works and other existing techniques, it is shown to be the best in both error and message capability. This technique is easy to model and simple to use and provides perfect security with unauthorized.
A Novel Technique for Image Steganography Based on DWT and Huffman EncodingCSCJournals
Image steganography is the art of hiding information into a cover image. This paper presents a novel technique for Image steganography based on DWT, where DWT is used to transform original image (cover image) from spatial domain to frequency domain. Firstly two dimensional Discrete Wavelet Transform (2-D DWT) is performed on a gray level cover image of size M × N and Huffman encoding is performed on the secret messages/image before embedding. Then each bit of Huffman code of secret message/image is embedded in the high frequency coefficients resulted from Discrete Wavelet Transform. Image quality is to be improved by preserving the wavelet coefficients in the low frequency sub-band. The experimental results show that the algorithm has a high capacity and a good invisibility. Moreover PSNR of cover image with stego-image shows the better results in comparison with other existing steganography approaches. Furthermore, satisfactory security is maintained since the secret message/image cannot be extracted without knowing decoding rules and Huffman table.
Implementation of LSB-Based Image Steganography Method for effectiveness of D...ijsrd.com
Increased use of electronic communication has given birth to new ways of transmitting information securely. Steganography is a science of hiding information by embedding it in some other data called host message. Images are most known objects for steganography. The host message before steganography and stego message after steganography have the same characteristics. The given work is to be done by evaluating it on MATALAB. While evaluation one can calculate SNR, PSNR and BER for individual information Bit for conceal bit and analysis effect on results.
Steganography using Coefficient Replacement and Adaptive Scaling based on DTCWTCSCJournals
Steganography is an authenticated technique for maintaining secrecy of embedded data. Steganography provides hardness of detecting the hidden data and has a potential capacity to hide the existence of confidential data. In this paper, we propose a novel steganography using coefficient replacement and adaptive scaling based on Dual Tree Complex Wavelet Transform (DTCWT) technique. The DTCWT and LWT 2 is applied on cover image and payload respectively to convert spatial domain into transform domain. The HH sub band coefficients of cover image are replaced by the LL sub band coefficients of payload to generate intermediate stego object and the adaptive scaling factor is used to scale down intermediate stego object coefficient values to generate final stego object. The adaptive scaling factor is determined based on entropy of cover image. The security and the capacity of the proposed method are high compared to the existing algorithms.
Research Inventy : International Journal of Engineering and Scienceresearchinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A novel hash based least significant bit (2 3-3) image steganography in spati...ijsptm
This paper presents a novel 2-3-3 LSB insertion method. The image steganography takes the advantage of human eye limitation. It uses color image as cover media for embedding secret message.The important quality of a steganographic system is to be less distortive while increasing the size of the secret message. In this paper a method is proposed to embed a color secret image into a color cover image. A 2-3-3 LSB insertion method has been used for image steganography. Experimental results show an improvement in the Mean squared error (MSE) and Peak Signal to Noise Ratio (PSNR) values of the proposed technique over the base technique of hash based 3-3-2 LSB insertion.
An image steganography using improved hyper-chaotic Henon map and fractal Tro...IJECEIAES
Steganography is a vital security approach that hides any secret content within ordinary data, such as multimedia. First, the cover image is converted into a wavelet environment using the integer wavelet transform (IWT), which protects the cover images from false mistakes. The grey wolf optimizer (GWO) is used to choose the pixel’s image that would be utilized to insert the hidden image in the cover image. GWO effectively selects pixels by calculating entropy, pixel intensity, and fitness function using the cover images. Moreover, the secret image was encrypted by utilizing a proposed hyper-chaotic improved Henon map and fractal Tromino. The suggested method increases computational security and efficiency with increased embedding capacity. Following the embedding algorithm of the secret image and the alteration of the cover image, the least significant bit (LSB) is utilized to locate the tempered region and to provide self-recovery characteristics in the digital image. According to the findings, the proposed technique provides a more secure transmission network with lower complexity in terms of peak signal-to-noise ratio (PSNR), normalized cross correlation (NCC), structural similarity index (SSIM), entropy and mean square error (MSE). As compared to the current approaches, the proposed method performed better in terms of PSNR 70.58% Db and SSIM 0.999 respectively.
Image steganography using least significant bit and secret map techniques IJECEIAES
In steganography, secret data are invisible in cover media, such as text, audio, video and image. Hence, attackers have no knowledge of the original message contained in the media or which algorithm is used to embed or extract such message. Image steganography is a branch of steganography in which secret data are hidden in host images. In this study, image steganography using least significant bit and secret map techniques is performed by applying 3D chaotic maps, namely, 3D Chebyshev and 3D logistic maps, to obtain high security. This technique is based on the concept of performing random insertion and selecting a pixel from a host image. The proposed algorithm is comprehensively evaluated on the basis of different criteria, such as correlation coefficient, information entropy, homogeneity, contrast, image, histogram, key sensitivity, hiding capacity, quality index, mean square error (MSE), peak signal-to-noise ratio (PSNR) and image fidelity. Results show that the proposed algorithm satisfies all the aforementioned criteria and is superior to other previous methods. Hence, it is efficient in hiding secret data and preserving the good visual quality of stego images. The proposed algorithm is resistant to different attacks, such as differential and statistical attacks, and yields good results in terms of key sensitivity, hiding capacity, quality index, MSE, PSNR and image fidelity.
Image compression using embedded zero tree waveletsipij
Compressing an image is significantly different than compressing raw binary data. compressing images is
used by this different compression algorithm. Wavelet transforms used in Image compression methods to
provide high compression rates while maintaining good image quality. Discrete Wavelet Transform (DWT)
is one of the most common methods used in signal and image compression .It is very powerful compared to
other transform because its ability to represent any type of signals both in time and frequency domain
simultaneously. In this paper, we will moot the use of Wavelet Based Image compression algorithm-
Embedded Zerotree Wavelet (EZW). We will obtain a bit stream with increasing accuracy from ezw
algorithm because of basing on progressive encoding to compress an image into . All the numerical results
were done by using matlab coding and the numerical analysis of this algorithm is carried out by sizing
Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR) for standard Lena Image .Experimental
results beam that the method is fast, robust and efficient enough to implement it in still and complex images
with significant image compression.
Optimized Reversible Data Hiding Technique for Secured Data TransmissionEditor IJMTER
Reversible data hiding (RDH) is used to embed secret message into a cover image by slightly
modifying its pixel values. Embedded message and the cover image are completely recovered from the
marked content. RDH supports information hiding with the lossless compressibility of natural images.
Lossless compression, difference expansion, histogram modification, prediction-error expansion and
integer transform techniques are used for RDH process. Histogram based RDH method is divided into
two steps histogram generation and histogram modification. Histogram construction is performed with
the pixel pairs sequences and their different values. Histogram modification is carried out to embed data
into the cover image. The un-hiding process recovers the message and also the cover image.
Reversible data hiding (RDH) scheme is designed by using difference-pair-mapping (DPM)
mechanism. A sequence consisting of pairs of difference values is computed by considering each pixelpair and its context. DPM is an injective mapping defined on difference-pairs. Specifically designed
DPM is used for Reversible data embedding process. A two-dimensional difference-histogram is
generated by counting the frequency of the resulting difference-pairs. Current histogram-based RDH
methods use natural extension of expansion embedding and shifting techniques. A pixel-pair-selection
strategy is adopted to use the pixel-pairs located in smooth image regions to embed data. Capacity
distortion property is used evaluate the embedding capacity (EC).
Two dimensional difference histogram modification model is enhanced to increase the
embedding capacity. Difference Pair Mapping (DPM) model is optimized to identify pixel redundancy.
Multiple in value based pixel pair modification is allowed in the system. Histogram modification is
carried out with different frequency levels.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
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A Secure Color Image Steganography in Transform Domain
1. International Journal on Cryptography and Information Security (IJCIS), Vol.3, No.1, March 2013
A SECURE COLOR IMAGE STEGANOGRAPHY IN
TRANSFORM DOMAIN
Hemalatha S1, U Dinesh Acharya2, Renuka A3, Priya R. Kamath4
1,2,3,4
Department of Computer Science and Engineering, Manipal Institute of Technology,
Manipal University, Manipal, Karnataka, India
1
hema.shama@manipal.edu;2dinesh.acharya@manipal.edu;3renuka.prabhu@manipa
l.edu;4priyarkamath@gmail.com
ABSTRACT
Steganography is the art and science of covert communication. The secret information can be concealed in
content such as image, audio, or video. This paper provides a novel image steganography technique to hide
both image and key in color cover image using Discrete Wavelet Transform (DWT) and Integer Wavelet
Transform (IWT). There is no visual difference between the stego image and the cover image. The extracted
image is also similar to the secret image. This is proved by the high PSNR (Peak Signal to Noise Ratio),
value for both stego and extracted secret image. The results are compared with the results of similar
techniques and it is found that the proposed technique is simple and gives better PSNR values than others.
KEYWORDS
Steganography, DWT, IWT, PSNR, YCbCr
1. INTRODUCTION
Recently, the information hiding technique has developed rapidly in the field of information
security and has received significant attention from both industry and academia. It contains two
main branches: digital watermarking and steganography. The former is mainly used for copyright
protection of electronic products while, the latter is a way of covert communication. The main
purpose of steganography is to convey the information secretly by concealing the very existence
of information in some other medium such as image, audio or video. The content used to embed
information is called as cover object. The cover along with the hidden information is called as
stego-object [1]. In this paper image is the cover and secret information is also an image. Both
secret image and stego key are embedded in the cover image to get stego image.
The major objective of steganography is to prevent some unintended observer from stealing or
destroying the confidential information. There are some factors to be considered when designing
a steganography system: [1]
• Invisibility: Invisibility is the ability to be unnoticed by the human.
• Security: Even if an attacker realizes the existence of the information in the stego object it
should be impossible for the attacker to detect the information. The closer the stego
image to the cover image, the higher the security. It is measured in terms of PSNR. High
PSNR value indicates high security.
PSNR = dB, where L = maximum value, MSE = Mean Square Error.
DOI:10.5121/ijcis.2013.3103 17
2. International Journal on Cryptography and Information Security (IJCIS), Vol.3, No.1, March 2013
MSE = , where X = original value, X’ = stego value and N = number of samples.
• Capacity: The amount of information that can be hidden relative to the size of the cover
object without deteriorating the quality of the cover object
• Robustness: It is the ability of the stego to withstand manipulations such as filtering,
cropping, rotation, compression etc.
The design of a steganographic system can be categorized into spatial domain methods and
transform domain methods [1].
In spatial domain methods, the processing is applied on the image pixel values directly. The
advantage of these methods is simplicity. The disadvantage is low ability to bear signal
processing operations. Least Significant Bit Insertion methods, Pallete based methods come under
this category.
In transform domain methods, the first step is to transform the cover image into different domain.
Then the transformed coefficients are processed to hide the secret information. These changed
coefficients are transformed back into spatial domain to get stego image. The advantage of
transform domain methods is the high ability to face signal processing operations. However,
methods of this type are computationally complex. Steganography methods using DCT (Discrete
Cosine Transforms), DWT, DFT (Discrete Fourier Transforms) come under this category.
1.1. Discrete Wavelet Transform
DWT is used for digital images. Many DWTs are available. Depending on the application
appropriate one should be used. The simplest one is haar transform. To hide text message integer
wavelet transform can be used. When DWT is applied to an image it is decomposed into 4 sub
bands: LL, HL, LH and HH. LL part contains the most significant features. So if the information
is hidden in LL part the stego image can withstand compression or other manipulations. But
sometimes distortion may be produced in the stego image and then other sub bands can be used
[1]. The decomposition of Lena image by 2 levels of 2D - DWT is shown in Figure 1.
Figure 1. 2 Level 2D – DWT
1.2. Integer Wavelet Transform
IWT is a more efficient approach to lossless compression. The coefficients in this transform are
represented by finite precision numbers which allows for lossless encoding. This wavelet
transform maps integers to integers. In case of DWT, if the input consists of integers (as in the
case of images), the resulting output no longer consists of integers. Thus the perfect
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3. International Journal on Cryptography and Information Security (IJCIS), Vol.3, No.1, March 2013
reconstruction of the original image becomes difficult. However, with the introduction of Wavelet
transforms that map integers to integers the output can be completely characterized with integers.
The LL sub-band in the case of IWT appears to be a close copy with smaller scale of the original
image while in the case of DWT the resulting LL sub-band is distorted slightly, as shown in
Figure 2.[2].
Figure 2 (a) Original image Lena. (b) One level DWT in sub band LL (c) One level IWT in sub-band LL.
If the original image (I) is X pixels high and Y pixels wide, the level of each of the pixel at (i,j) is
denoted by Ii,j.[3]
The IWT coefficients are given by
LLi,j = ( I2i, 2j + I 2i+1, 2j) /2 (1)
HLi,j = I2i+1, 2j - I2i, 2j (2)
LHi,j = I2i, 2j+1 - I2i, 2j (3)
HHi,j = I2i+1, 2j +1 - I2i, 2j (4)
The inverse transform is given by
I2i, 2j = LLi,j - HLi,j/2 (5)
I2i, 2j +1 = LLi,j + (HLi,j+1)/2 (6)
I2i+1, 2j = I2i, 2j +1 + LHi,j - HLi,j (7)
I2i+1, 2j+1 = I2i+1,2j + HHi,j - LHi,j (8)
where, 1 ≤ i ≤ X/2 , 1 ≤ j ≤ Y/2 and denotes floor value.
2. RELATED WORK
Color images are represented in different color spaces such as RGB (Red Green Blue), HSV
(Hue, Saturation, Value), YUV, YIQ, YCbCr (Luminance/Chrominance) etc. YCbCr is one of the
best representations for steganography because the eye is sensitive to small changes in luminance
but not in chrominance, so the chrominance part can be altered, without visually impairing the
overall image quality much. Y is luminance component and CbCr are the blue and red
chrominance components respectively. The values in one color space can be easily converted into
another color space using conversion formula [4].
S. M. Masud Karim, et al., [5] proposed a new approach based on LSB using secret key. The
secret key encrypts the hidden information and then it is stored into different position of LSB of
image. This provides very good security. XIE Qing et al.,[6] proposed a method in which the
information is hidden in all RGB planes based on HVS (Human Visual System). This degrades
the quality of the stego image. In the method proposed by Sunny Sachdeva et al., [7] the Vector
Quantization (VQ) table is used to hide the secret message which increases the capacity and also
stego size. Sankar Roy et al., [8] proposed an improved steganography approach for hiding text
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4. International Journal on Cryptography and Information Security (IJCIS), Vol.3, No.1, March 2013
messages within lossless RGB images which will suffer from withstanding the signal processing
operations. Minimum deviation of fidelity based data embedding technique has been proposed by
J. K. Mandal et al, [9] where two bits per byte have been replaced by choosing the position
randomly between LSB and up to fourth bit towards MSB. A DWT based frequency domain
steganographic technique, termed as WTSIC is also proposed by the same authors, [10] where
secret message/image bits stream are embedded in horizontal, vertical and diagonal components.
Anjali Sejul, et al, [4] proposed an algorithm in which binary images are considered to be secret
images which are embedded inside the cover image by taking the HSV (Hue, Saturation, Value)
values of the cover image into consideration. The secret image is inserted into the cover image by
cropping the cover image according to the skin tone detection and then applying the DWT. In this
method the capacity is too low.
El Safy et.al, [11], used an adaptive steganographic technique based on IWT, which improves the
hiding capacity and PSNR. Neda Raftari and Amir Masoud E. M. [12] used IWT and Munkres'
assignment algorithm which embeds secret image in frequency domain of cover image with high
matching quality. The improvement is obtained with higher computation. Saddaf Rubab et
al.,[13] proposed a complex method using DWT and Blowfish encryption technique to hide text
message in color image. In the paper by Kapre Bhagyashri et al, [14] a new singular value
decomposition (SVD) and DWT based water mark technique is proposed in full frequency band
in YUV color space. Nabin Ghoshal et al., uses a steganographic scheme for colour image
authentication (SSCIA) [15] where the watermark image is embedded using DFT.
The proposed work is the extension of our previous work [16] to color images in which the secret
image is transmitted without actually embedding in the cover image. Only the key is hidden in the
cover image. The steps for embedding are as follows:
• Obtain single level 2D DWT of the cover-image C and secret-image S.
• The resulting transformed matrix consists of four sub-bands CLL, CHL, CLH and CHH
and SLL, SHL, SLH and SHH obtained by transforming images C and S respectively.
• The sub-images CLL and SLL are subdivided into non-overlapping blocks BCk1 (1 ≤ k1
< nc) and BSi (1 ≤ i < ns) of size 2x2 where nc, ns are the total number of non-
overlapping blocks obtained from sub-images CLL and SLL respectively.
• Every block BSi, is compared with block BCk1. The pair of blocks which have the least
Root Mean Square Error is determined. A key is used to determine the address of the best
matched block BCk1 for the block BSi. Then inverse 2D DWT is applied to obtain C.
• The Key is then stored using one of the spatial domain techniques in the cover image C.
The simplest of the spatial domain techniques is LSB insertion algorithm.
• The resultant image is a stego-image.
•
The secret image can now be extracted from this image by following the steps mentioned below:
• From the stego-image G, obtain the secret key K1
• Transform the stego-image into single level 2D DWT.
• This transformation results in four sub-bands GLL, GHL, GLH and GHH.
• Divide the sub-band image GLL into 2x2 non-overlapping blocks. The secret key K1 is
used to obtain the blocks that have the nearest approximation to the original blocks in
secret image.
• The obtained blocks are then rearranged to obtain the sub-band image SLLnew.
Assuming SHLnew, SLHnew, SHHnew are zero matrices of dimension similar to
SLLnew , 2D IDWT (Inverse DWT) is obtained.
• The resultant image is the secret image that was originally intended to be embedded
within the cover-image.
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5. International Journal on Cryptography and Information Security (IJCIS), Vol.3, No.1, March 2013
3. PROPOSED METHOD
In the proposed method, the cover is 256x256 lena color image. The secret information is grey
scale image of size 128 x128. To transfer the secret image confidentially, the secret image itself is
not hidden, instead a key is generated and then the key is encrypted and Run Length Encoded.
The resultant key is hidden in the cover image using Integer Wavelet Transform (IWT). This
improves the security and also the capacity can be improved to some extent since the key is
compressed.
3.1. Key Generation
To generate the key following steps are performed.
• Represent the cover image C in YCbCr color space
• Obtain single level 2D DWT of secret-image S and Cr component of C.
• The resulting transformed matrix consists of four sub-bands SLL, SHL, SLH and SHH
and CLL, CHL, CLH and CHH obtained by transforming S and Cr component of C
respectively. After this the steps are same as our previous work, which are repeated again
for better understanding.
• The sub-images CLL and SLL are subdivided into non-overlapping blocks BCk1 (1 ≤ k1
< nc) and BSi (1 ≤ i < ns) of size 2x2 where nc, ns are the total number of non-
overlapping blocks obtained from sub-images CLL and SLL respectively.
• Every block BSi, is compared with block BCk1. The pair of blocks which have the least
Root Mean Square Error is determined. A key is used to determine the address of the best
matched block BCk1 for the block BSi. Then inverse 2D DWT is applied to obtain Cr
component.
• The key is then encrypted using simple exclusive or operation with a key and run length
encoded.
3.2. Key Embedding
The key obtained in the previous subsection is hidden in the cover image using IWT. The steps
are as follows:
• Find the integer wavelet transform of Cr component of the cover image.
• Replace the least significant bit planes of the higher frequency components of the
transformed image by the bits of the key.
• Obtain the inverse IWT of the resulting image to get the stego Cr component.
• Represent the resultant image in RGB color space to obtain stego image G.
The secret image can now be extracted from this image using the following steps:
3.3. Key Extraction
The steps are as follows:
• Represent the stego image G in YCbCr color space.
• Find the integer wavelet transform of Cr component of the stego image G
• Obtain the key from the least significant bit planes of the higher frequency components of
the transformed image. Convert back to RGB representation.
• Decompress the key and then decrypt it to get original key.
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6. International Journal on Cryptography and Information Security (IJCIS), Vol.3, No.1, March 2013
3.4. Secret Image Generation
To generate the secret image following steps are performed
• Transform the stego-image G into single level 2D DWT.
• This transformation results in four sub-bands GLL, GHL, GLH and GHH.
• Divide the sub-band image GLL into 2x2 non-overlapping blocks. The key is used to
obtain the blocks that have the nearest approximation to the original blocks in secret
image.
• The obtained blocks are then rearranged to obtain the sub-band image SLLnew.
Assuming SHLnew, SLHnew, SHHnew are zero matrices of dimension similar to
SLLnew, 2D IDWT is obtained.
• The resultant image is the secret image S.
4. EXPERIMENTAL RESULTS
The algorithm is tested in MATLAB with Cr component of the cover image. The results with
different cover images and secret images are shown. Original cover and secret images are shown
in Figure 3 and Figure 4 respectively. Football is hidden in lena, earth is hidden in peppers and
moon is hidden in baboon. The cover image size is 256x256 and secret image size is 128x128.
Figure 3. Color images that are used as cover images: (a) lena (b) baboon (c) peppers
Figure 4. Images which are used as secret images: (a) earth (b) football (c) moon
The stego and extracted secret images are shown in Figure 5 and Figure 6 respectively.
Figure 5. Stego images: (a) football, (b) earth, (c) moon as secret images
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7. International Journal on Cryptography and Information Security (IJCIS), Vol.3, No.1, March 2013
Figure 6. Extracted Secret images: (a) football (b) earth (c) moon
The PSNR in dB in all cases for stego and extracted secret images are tabulated in Tables 1 and 2
respectively.
Table 1. PSNR (in dB) of the stego image
COVER IMAGE (256x256) SECRET IMAGE(128x128)
football earth moon
lena 44.3 44.4 44.2
peppers 44.7 44.7 45.0
baboon 44.8 44.8 45.0
Table 2. PSNR (in dB) of the extracted secret image
COVER IMAGE (256x256) SECRET IMAGE(128x128)
football earth moon
lena 37.5 34.1 30.7
peppers 30.4 28.6 26.7
baboon 37.2 27.6 36.5
Table 3 compares the PSNR values in the proposed method and that in the other four methods. In
all these the cover image considered is lena image and the secret images used are of comparable
sizes.
Table 3. Comparison of PSNR (in dB) of the stego image in different methods
TECHNIQUE PSNR
Mandal, J.K. et al. [9] 39.6
Mandal, J.K. et al. [10] 42.4
Kapre Bhagyashri, S. et al. [14] 36.6
Ghoshal, N. et al. [15] 33.2
PROPOSED 44.3
5. CONCLUSIONS
In this paper, we observe that the secret image can be regenerated without actually storing the
image itself. This approach results in high quality of the stego-image having high PSNR values
compared to other methods. Instead of taking the least significant bit plane to hide the key middle
bit planes can be considered to improve the security. One assumption made in this paper is that
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8. International Journal on Cryptography and Information Security (IJCIS), Vol.3, No.1, March 2013
the encryption key is sent to the recepient by some means. Standard encryption techniques like
Blowfish or RC6 can be used to encrypt the key so that the security can be further improved. The
encryption key also has to be hidden in the cover image.
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