The Least Significant Bit (LSB) algorithm and the Most Significant Bit (MSB) algorithm are stenography algorithms with each one having its demerits. This work therefore proposed a Hybrid approach and compared its efficiency with LSB and MSB algorithms. The Least Significant Bit (LSB) and Most
Significant Bit (MSB) techniques were combined in the proposed algorithm. Two bits (the least significant bit and the most significant bit) of the cover images were replaced with a secret message. Comparisons were made based on Mean-Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and the encoding time between the proposed algorithm, LSB and MSB after embedding in digital images. The combined
technique produced a stego-image with minimal distortion in image quality than MSB technique independent of the nature of data that was hidden. However, LSB algorithm produced the best stego-image quality. Large cover images however made the combined algorithm’s quality better improved. The combined algorithm had lesser time of image and text encoding. Therefore, a trade-off exists between the encoding time and the quality of stego-image as demonstrated in this work.
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.
Information Hiding using LSB Technique based on Developed PSO Algorithm IJECEIAES
Generally, The sending process of secret information via the transmission channel or any carrier medium is not secured. For this reason, the techniques of information hiding are needed. Therefore, steganography must take place before transmission. To embed a secret message at optimal positions of the cover image under spatial domain, using the developed particle swarm optimization algorithm (Dev.-PSO) to do that purpose in this paper based on Least Significant Bits (LSB) using LSB substitution. The main aim of (Dev. -PSO) algorithm is determining an optimal paths to reach a required goals in the specified search space based on disposal of them, using (Dev.-PSO) algorithm produces the paths of a required goals with most efficient and speed. An agents population is used in determining process of a required goals at search space for solving of problem. The (Dev.-PSO) algorithm is applied to different images; the number of an image which used in the experiments in this paper is three. For all used images, the Peak Signal to Noise Ratio (PSNR) value is computed. Finally, the PSNR value of the stego-A that obtained from blue sub-band colo is equal (44.87) dB, while the stego-B is equal (44.45) dB, and the PSNR value for the stego-C is (43.97)dB, while the vlue of MSE that obtained from the same color subbans is (0.00989), stego-B equal to (0.01869), and stego-C is (0.02041). Furthermore, our proposed method has ability to survive the quality for the stego image befor and after hiding stage or under intended attack that used in the existing paper such as Gaussian noise, and salt & pepper noise.
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
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.
Information Hiding using LSB Technique based on Developed PSO Algorithm IJECEIAES
Generally, The sending process of secret information via the transmission channel or any carrier medium is not secured. For this reason, the techniques of information hiding are needed. Therefore, steganography must take place before transmission. To embed a secret message at optimal positions of the cover image under spatial domain, using the developed particle swarm optimization algorithm (Dev.-PSO) to do that purpose in this paper based on Least Significant Bits (LSB) using LSB substitution. The main aim of (Dev. -PSO) algorithm is determining an optimal paths to reach a required goals in the specified search space based on disposal of them, using (Dev.-PSO) algorithm produces the paths of a required goals with most efficient and speed. An agents population is used in determining process of a required goals at search space for solving of problem. The (Dev.-PSO) algorithm is applied to different images; the number of an image which used in the experiments in this paper is three. For all used images, the Peak Signal to Noise Ratio (PSNR) value is computed. Finally, the PSNR value of the stego-A that obtained from blue sub-band colo is equal (44.87) dB, while the stego-B is equal (44.45) dB, and the PSNR value for the stego-C is (43.97)dB, while the vlue of MSE that obtained from the same color subbans is (0.00989), stego-B equal to (0.01869), and stego-C is (0.02041). Furthermore, our proposed method has ability to survive the quality for the stego image befor and after hiding stage or under intended attack that used in the existing paper such as Gaussian noise, and salt & pepper noise.
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
Design and Implementation of Lifting Based Wavelet and Adaptive LSB Steganogr...Dr. Amarjeet Singh
Image steganography is an art of hiding images
secretly within another image. There are several ways of
performing image steganography; one among them is the
spatial approach. The most popular spatial domain approach
of image steganography is the Least Significant Bit (LSB)
method, which hides the secret image pixel information in the
LSB of the cover image pixel information. In this paper a
LSB based steganography approach is used to design
hardware architecture for the Image steganography. The
Discrete Wavelet Transform (DWT) is used here to transform
the cover image into higher and lower wavelet coefficients
and use these coefficients in hiding the secret image. the
design also includes encryption of secret image data, to
provide a higher level of security to the secret image. The
steganography system involving the stegno module and a
decode module is designed here. The design was simulated,
synthesized and implemented on Artix -7 FPGA. The
operation hiding and retrieving images was successfully
verified through simulations.
A novel secure image steganography method based on chaos theory in spatial do...ijsptm
This paper presents a novel approach of building a secure data hiding technique in digital images. The
image steganography technique takes the advantage of limited power of human visual system (HVS). It uses
image as cover media for embedding secret message. The most important requirement for a steganographic
algorithm is to be imperceptible while maximizing the size of the payload. In this paper a method is
proposed to encrypt the secret bits of the message based on chaos theory before embedding into the cover
image. A 3-3-2 LSB insertion method has been used for image steganography. Experimental results show a
substantial improvement in the Peak Signal to Noise Ratio (PSNR) and Image Fidelity (IF) value of the
proposed technique over the base technique of 3-3-2 LSB insertion.
A new image steganography algorithm basedIJNSA Journal
In recent years, the rapid growth of information technology and digital communication has become very
important to secure information transmission between the sender and receiver. Therefore, steganography
introduces strongly to hide information and to communicate a secret data in an appropriate multimedia
carrier, e.g., image, audio and video files. In this paper, a new algorithm for image steganography has
been proposed to hide a large amount of secret data presented by secret color image. This algorithm is
based on different size image segmentations (DSIS) and modified least significant bits (MLSB), where the
DSIS algorithm has been applied to embed a secret image randomly instead of sequentially; this approach
has been applied before embedding process. The number of bit to be replaced at each byte is non uniform,
it bases on byte characteristics by constructing an effective hypothesis. The simulation results justify that
the proposed approach is employed efficiently and satisfied high imperceptible with high payload capacity
reached to four bits per byte.
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.
Steganography is a technique of concealing the secret information in a digital carrier media, so that only
the authorized recipient can detect the presence of secret information. In this paper, we propose a spatial
domain steganography method for embedding secret information on conditional basis using 1-Bit of Most
Significant Bit (MSB). The cover image is decomposed into blocks of 8*8 matrix size. The first block of
cover image is embedded with 8 bits of upper bound and lower bound values required for retrieving
payload at the destination. The mean of median values and difference between consecutive pixels of each
8*8 block of cover image is determined to embed payload in 3 bits of Least Significant Bit (LSB) and 1 bit
of MSB based on prefixed conditions. It is observed that the capacity and security is improved compared to
the existing methods with reasonable PSNR.
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.
On Text Realization Image SteganographyCSCJournals
In this paper the steganography strategy is going to be implemented but in a different way from a different scope since the important data will neither be hidden in an image nor transferred through the communication channel inside an image, but on the contrary, a well known image will be used that exists on both sides of the channel and a text message contains important data will be transmitted. With the suitable operations, we can re-mix and re-make the source image. MATLAB7 is the program where the algorithm implemented on it, where the algorithm shows high ability for achieving the task to different type and size of images. Perfect reconstruction was achieved on the receiving side. But the most interesting is that the algorithm that deals with secured image transmission transmits no images at all
Improved LSB Steganograhy Technique for grayscale and RGB imagesIJERA Editor
A number of techniques are there to converse securely. Encryption and cryptography are enabling us to have a secure conversation. To protect privacy and communicate in an undetectable way it is required to use some steganography technique. This is to hide messages in some other media generally called cover object. In todays digital world where images are a common means of information sharing, most of the steganography techniques use digital images as a carrier for hiding message. In this paper a LSB based technique is proposed for steganograpgy. This technique is different from standard LSB technique that along with message hidden in LSB bits a part of message also resides at other selective bits using a key. The method is developed to increase the payload capacity and make detection impossible.
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
We follow "Rigorous Publication" model - means that all articles appear on IJERD after full appraisal, effectiveness, legitimacy and reliability of research content. International Journal of Engineering Research and Development publishes papers online as well as provide hard copy of Journal to authors after publication of paper. It is intended to serve as a forum for researchers, practitioners and developers to exchange ideas and results for the advancement of Engineering & Technology.
A new partial image encryption method for document images using variance base...IJECEIAES
The proposed method partially and completely encrypts the gray scale Document images. The complete image encryption is also performed to compare the performance with the existing encryption methods. The partial encryption is carried out by segmenting the image using the Quad-tree decomposition method based on the variance of the image block. The image blocks with uniform pixel levels are considered insignificant blocks and others the significant blocks. The pixels in the significant blocks are permuted by using 1D Skew tent chaotic map. The partially encrypted image blocks are further permuted using 2D Henon map to increase the security level and fed as input to complete encryption. The complete encryption is carried out by diffusing the partially encrypted image. Two levels of diffusion are performed. The first level simply modifies the pixels in the partially encrypted image with the Bernoulli’s chaotic map. The second level establishes the interdependency between rows and columns of the first level diffused image. The experiment is conducted for both partial and complete image encryption on the Document images. The proposed scheme yields better results for both partial and complete encryption on Speed, statistical and dynamical attacks. The results ensure better security when compared to existing encryption schemes.
A Secure & Optimized Data Hiding Technique Using DWT With PSNR ValueIJERA Editor
Multimedia applications are becoming increasingly significant in modern world. The mushroom growth of multimedia data of these applications, particularly over the web has increased the demand for protection of copyright. Digital watermarking is much more acceptable as a solution to the problem of copyright protection and authentication of multimedia data while working in a networked environment. In this paper, a DWT based watermarking scheme is proposed. We have used Genetic Algorithm (GA) in order to make an optimum tradeoff between imperceptibility and robustness by choosing an optimum watermarking level for each coefficient of the cover image. In addition to the suitable watermarking strength, the selection of best block size is also necessary for superior perceptual shaping functions. To achieve this goal we have trained and used GA to pick the best block size to tailor the watermark in one of the coefficients of the DWT. The fitness function criterion for the genetic algorithm decision making is based on PSNR values
Cloud computing is a powerful, flexible, cost
efficient platform for providing consumer IT services
over the Internet. However Cloud Computing has
various level of risk because most important
information is maintained and managed by third party
vendors, which means harder to maintain security for
user’s data .Steganography is one of the ways to provide
security for secret data by inserting in an image or
video. In this most of the algorithms are based on the
Least Significant Bit (LSB), but the hackers easily
detects it embeds directly. An Efficient and secure
method of embedding secret message-extracting
message into or from color image using Artificial
Neural Network will be proposed. The proposed
method will be tested, implemented and analyzed for
various color images of different sizes and different
sizes of secret messages. The performance of the
algorithm will be analyzed by calculating various
parameters like PSNR, MSE and the results are good
compared to existing algorithms.
In recent time, the Steganography technique is broadly used for the secret data communication. It’s an art of hiding the secret data in another objects like videos, images, videos, graphics and documents to gain the stego or steganographic object so which it’s not affected by the insertion. In this paper, we are introducing a new methodology in which security of stego-image increase by embedding even and odd part secret image into R, G, B plane of cover image using LSB and ISB technique. As we can see from the results session the value of PSNR , NCC are getting increase while the value of MSE is getting decrease.
Design of an adaptive JPEG Steganalysis with UED IJCERT JOURNAL
Steganography is the art and science of writing hidden messages in such a way that no one apart from the sender and intended recipient suspects the existence of the message a form of security through obscurity. The internet as a whole does not use secure links, thus information in transit may be vulnerable to interception as well. The important of reducing a chance of the information being detected during the transmission is being an issue now days. In this paper, we proposed a class of new distortion functions known as uniform embedding distortion function (UED) is presented. By incorporating the syndrome trellis coding, the best code word with undetectable data hiding is achieved. Due to hiding more amounts of data into the intersected area, embedding capacity is increased. Our aim is to hide the secret information behind the image file. Steganography hides the secret message so that intruder’s can’t detect the communication. When hiding data into the intersected area, thus provides a higher level of security with more efficient data mean square error is reduced and embedding capacity is increased.
Imbalance datasets impose serious problems in machine learning. For many tasks characterized by imbalanced data, the F-Measure seems more appropiate than the Mean Square Error or other relative error measures. This paper studies the use of F-Measure as the training criterion for Neural Networks by integrating it in the Backpropagation algorithm. This novel training criterion has been validated empirically on a real task for which F-Measure is typically applied to evaluate the quality. The task consists in cleaning and enhancing ancient document images which is performed, in this work, by means of neural filters.
Design and Implementation of Lifting Based Wavelet and Adaptive LSB Steganogr...Dr. Amarjeet Singh
Image steganography is an art of hiding images
secretly within another image. There are several ways of
performing image steganography; one among them is the
spatial approach. The most popular spatial domain approach
of image steganography is the Least Significant Bit (LSB)
method, which hides the secret image pixel information in the
LSB of the cover image pixel information. In this paper a
LSB based steganography approach is used to design
hardware architecture for the Image steganography. The
Discrete Wavelet Transform (DWT) is used here to transform
the cover image into higher and lower wavelet coefficients
and use these coefficients in hiding the secret image. the
design also includes encryption of secret image data, to
provide a higher level of security to the secret image. The
steganography system involving the stegno module and a
decode module is designed here. The design was simulated,
synthesized and implemented on Artix -7 FPGA. The
operation hiding and retrieving images was successfully
verified through simulations.
A novel secure image steganography method based on chaos theory in spatial do...ijsptm
This paper presents a novel approach of building a secure data hiding technique in digital images. The
image steganography technique takes the advantage of limited power of human visual system (HVS). It uses
image as cover media for embedding secret message. The most important requirement for a steganographic
algorithm is to be imperceptible while maximizing the size of the payload. In this paper a method is
proposed to encrypt the secret bits of the message based on chaos theory before embedding into the cover
image. A 3-3-2 LSB insertion method has been used for image steganography. Experimental results show a
substantial improvement in the Peak Signal to Noise Ratio (PSNR) and Image Fidelity (IF) value of the
proposed technique over the base technique of 3-3-2 LSB insertion.
A new image steganography algorithm basedIJNSA Journal
In recent years, the rapid growth of information technology and digital communication has become very
important to secure information transmission between the sender and receiver. Therefore, steganography
introduces strongly to hide information and to communicate a secret data in an appropriate multimedia
carrier, e.g., image, audio and video files. In this paper, a new algorithm for image steganography has
been proposed to hide a large amount of secret data presented by secret color image. This algorithm is
based on different size image segmentations (DSIS) and modified least significant bits (MLSB), where the
DSIS algorithm has been applied to embed a secret image randomly instead of sequentially; this approach
has been applied before embedding process. The number of bit to be replaced at each byte is non uniform,
it bases on byte characteristics by constructing an effective hypothesis. The simulation results justify that
the proposed approach is employed efficiently and satisfied high imperceptible with high payload capacity
reached to four bits per byte.
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.
Steganography is a technique of concealing the secret information in a digital carrier media, so that only
the authorized recipient can detect the presence of secret information. In this paper, we propose a spatial
domain steganography method for embedding secret information on conditional basis using 1-Bit of Most
Significant Bit (MSB). The cover image is decomposed into blocks of 8*8 matrix size. The first block of
cover image is embedded with 8 bits of upper bound and lower bound values required for retrieving
payload at the destination. The mean of median values and difference between consecutive pixels of each
8*8 block of cover image is determined to embed payload in 3 bits of Least Significant Bit (LSB) and 1 bit
of MSB based on prefixed conditions. It is observed that the capacity and security is improved compared to
the existing methods with reasonable PSNR.
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.
On Text Realization Image SteganographyCSCJournals
In this paper the steganography strategy is going to be implemented but in a different way from a different scope since the important data will neither be hidden in an image nor transferred through the communication channel inside an image, but on the contrary, a well known image will be used that exists on both sides of the channel and a text message contains important data will be transmitted. With the suitable operations, we can re-mix and re-make the source image. MATLAB7 is the program where the algorithm implemented on it, where the algorithm shows high ability for achieving the task to different type and size of images. Perfect reconstruction was achieved on the receiving side. But the most interesting is that the algorithm that deals with secured image transmission transmits no images at all
Improved LSB Steganograhy Technique for grayscale and RGB imagesIJERA Editor
A number of techniques are there to converse securely. Encryption and cryptography are enabling us to have a secure conversation. To protect privacy and communicate in an undetectable way it is required to use some steganography technique. This is to hide messages in some other media generally called cover object. In todays digital world where images are a common means of information sharing, most of the steganography techniques use digital images as a carrier for hiding message. In this paper a LSB based technique is proposed for steganograpgy. This technique is different from standard LSB technique that along with message hidden in LSB bits a part of message also resides at other selective bits using a key. The method is developed to increase the payload capacity and make detection impossible.
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
We follow "Rigorous Publication" model - means that all articles appear on IJERD after full appraisal, effectiveness, legitimacy and reliability of research content. International Journal of Engineering Research and Development publishes papers online as well as provide hard copy of Journal to authors after publication of paper. It is intended to serve as a forum for researchers, practitioners and developers to exchange ideas and results for the advancement of Engineering & Technology.
A new partial image encryption method for document images using variance base...IJECEIAES
The proposed method partially and completely encrypts the gray scale Document images. The complete image encryption is also performed to compare the performance with the existing encryption methods. The partial encryption is carried out by segmenting the image using the Quad-tree decomposition method based on the variance of the image block. The image blocks with uniform pixel levels are considered insignificant blocks and others the significant blocks. The pixels in the significant blocks are permuted by using 1D Skew tent chaotic map. The partially encrypted image blocks are further permuted using 2D Henon map to increase the security level and fed as input to complete encryption. The complete encryption is carried out by diffusing the partially encrypted image. Two levels of diffusion are performed. The first level simply modifies the pixels in the partially encrypted image with the Bernoulli’s chaotic map. The second level establishes the interdependency between rows and columns of the first level diffused image. The experiment is conducted for both partial and complete image encryption on the Document images. The proposed scheme yields better results for both partial and complete encryption on Speed, statistical and dynamical attacks. The results ensure better security when compared to existing encryption schemes.
A Secure & Optimized Data Hiding Technique Using DWT With PSNR ValueIJERA Editor
Multimedia applications are becoming increasingly significant in modern world. The mushroom growth of multimedia data of these applications, particularly over the web has increased the demand for protection of copyright. Digital watermarking is much more acceptable as a solution to the problem of copyright protection and authentication of multimedia data while working in a networked environment. In this paper, a DWT based watermarking scheme is proposed. We have used Genetic Algorithm (GA) in order to make an optimum tradeoff between imperceptibility and robustness by choosing an optimum watermarking level for each coefficient of the cover image. In addition to the suitable watermarking strength, the selection of best block size is also necessary for superior perceptual shaping functions. To achieve this goal we have trained and used GA to pick the best block size to tailor the watermark in one of the coefficients of the DWT. The fitness function criterion for the genetic algorithm decision making is based on PSNR values
Cloud computing is a powerful, flexible, cost
efficient platform for providing consumer IT services
over the Internet. However Cloud Computing has
various level of risk because most important
information is maintained and managed by third party
vendors, which means harder to maintain security for
user’s data .Steganography is one of the ways to provide
security for secret data by inserting in an image or
video. In this most of the algorithms are based on the
Least Significant Bit (LSB), but the hackers easily
detects it embeds directly. An Efficient and secure
method of embedding secret message-extracting
message into or from color image using Artificial
Neural Network will be proposed. The proposed
method will be tested, implemented and analyzed for
various color images of different sizes and different
sizes of secret messages. The performance of the
algorithm will be analyzed by calculating various
parameters like PSNR, MSE and the results are good
compared to existing algorithms.
In recent time, the Steganography technique is broadly used for the secret data communication. It’s an art of hiding the secret data in another objects like videos, images, videos, graphics and documents to gain the stego or steganographic object so which it’s not affected by the insertion. In this paper, we are introducing a new methodology in which security of stego-image increase by embedding even and odd part secret image into R, G, B plane of cover image using LSB and ISB technique. As we can see from the results session the value of PSNR , NCC are getting increase while the value of MSE is getting decrease.
Design of an adaptive JPEG Steganalysis with UED IJCERT JOURNAL
Steganography is the art and science of writing hidden messages in such a way that no one apart from the sender and intended recipient suspects the existence of the message a form of security through obscurity. The internet as a whole does not use secure links, thus information in transit may be vulnerable to interception as well. The important of reducing a chance of the information being detected during the transmission is being an issue now days. In this paper, we proposed a class of new distortion functions known as uniform embedding distortion function (UED) is presented. By incorporating the syndrome trellis coding, the best code word with undetectable data hiding is achieved. Due to hiding more amounts of data into the intersected area, embedding capacity is increased. Our aim is to hide the secret information behind the image file. Steganography hides the secret message so that intruder’s can’t detect the communication. When hiding data into the intersected area, thus provides a higher level of security with more efficient data mean square error is reduced and embedding capacity is increased.
Imbalance datasets impose serious problems in machine learning. For many tasks characterized by imbalanced data, the F-Measure seems more appropiate than the Mean Square Error or other relative error measures. This paper studies the use of F-Measure as the training criterion for Neural Networks by integrating it in the Backpropagation algorithm. This novel training criterion has been validated empirically on a real task for which F-Measure is typically applied to evaluate the quality. The task consists in cleaning and enhancing ancient document images which is performed, in this work, by means of neural filters.
Images may contain different types of noises. Removing noise from image is often the first step in image processing, and remains a challenging problem in spite of sophistication of recent research. This ppt presents an efficient image denoising scheme and their reconstruction based on Discrete Wavelet Transform (DWT) and Inverse Discrete Wavelet Transform (IDWT).
In economical societies of today, using cash is an inseparable aspect of human’s life. People use cash for
marketing, services, entertainments, bank operations and so on. This huge amount of contact with cash and
the necessity of knowing the monetary value of it caused one of the most challenging problems for visually
impaired people. In this paper we propose a mobile phone based approach to identify monetary value of a
picture taken from a banknote using some image processing and machine vision techniques. While the
developed approach is very fast, it can recognize the value of the banknote by an average accuracy rate of
about 97% and can overcome different challenges like rotation, scaling, collision, illumination changes,
perspective, and some others.
A privacy learning objects identity system for smartphones based on a virtu...ijcsit
Smartphones are widely used today, with many features such as GPS map navigation, capturing
photos with camera equipment such as digital camera, internet connection via wifi or 3G devices that
function as computers. These devices are being used for various purposes including online learning, where
learners can study from anywhere and anytime for example in the street, home, office and school. However,
identifing a method by which teachers in these virtural environements can remember their learners “faces”
in the classroom or manage "Identification Number Student" (ID student or user) is not reliable when the
teacher cannot see all of the learners in the class or know who is online from a particular account. In this
paper, we propose a system, Android Virtual Learner Identify (AVLI), which collects images captured by
the face of the learning object directly from the camera, the location of the learner by identifing where the
learner is studying and configuration of information including Time, Mac, IP addresses, IMEI number and
location via GPS. The systen then saves learner profiles to help the teacher or education managers on the
Virtual Learning Environment (VLE) identify learning object. We used the VLE that we built on
mobile.ona.vn domain. We implemented the AVLI prototype Android phone with solution password
encryption and images taken directly from the camera to ensure that the information is transmitted and
stored securely in the Virtual Learning Environment System Database (VLE Data) of learning objects while
preserving the ability to identify learning objects by a teacher or education manager.
Massive parallelism with gpus for centrality ranking in complex networksijcsit
Many problems in Computer Science can be modelled using graphs. Evaluating node centrality in complex
networks, which can be considered equivalent to undirected graphs, provides an useful metric of the
relative importance of each node inside the evaluated network. The knowledge on which the most central
nodes are, has various applications, such as improving information spreading in diffusion networks. In this
case, most central nodes can be considered to have higher influence rates over other nodes in the network.
The main purpose in this work is developing a GPU based and massively parallel application so as to
evaluate the node centrality in complex networks using the Nvidia CUDA programming model. The main
contribution of this work is the strategies for the development of an algorithm to evaluate the node
centrality in complex networks using Nvidia CUDA parallel programming model. We show that the
strategies improves algorithm´s speed-up in two orders of magnitude on one NVIDIA Tesla k20 GPU
cluster node, when compared to the hybrid OpenMP/MPI algorithm version, running in the same cluster,
with 4 nodes 2 Intel(R) Xeon(R) CPU E5-2660 each, for radius zero
Artificial intelligence handling through teaching and learning process and it...ijscai
According to this fact that educational system is the base of constant development in every country and this
system educates human-forces and this forces,are accelerators and a factor, of achieving the goals of
development,the educational system can play, Major role in the context economic behavior, in this context
some concepts are regarded as behavioral targets and performance.In educational system, handling
artificial intelligence, in teaching and learning process, had a surprising evolution through educational
advantages, making job, respecting customers rights and customer relationship management, to assist
priority and citizenship, correct investment through formal markets. Science-Based economy, resistible
economy and a positive view to job and Iran capital,including concepts which can be institutionalize in to
the educational system. In this paper it is decided to pose a new method, creating a proper cultural and
scientific bed, this helps.That the educational system behavioral goals, better and stable being achieved.
The method presented in this paper is general and based on handling artificial intelligence, information
technology and electronic content management that means in an intelligent educational system.The
educational goals can be better achieved and managed by new technology of education.
In this paper, we presented a method to retrieve documents with unstructured text data written in different
languages. Apart from the ordinary document retrieval systems, the proposed system can also process
queries with terms in more than one language. Unicode, the universally accepted encoding standard is used
to present the data in a common platform while converting the text data into Vector Space Model. We got
notable F measure values in the experiments irrespective of languages used in documents and queries.
Functional requirements of intelligent object frameworkijscai
Intelligent Object Framework (IOF) is a new communication standard over a wireless network supporting
existing multiple sets of architectural solutions. The Framework consists of a framework design that
enables devices of different platforms to communicate by a common data exchange model via a device
management controller. This paper provides a descriptive analysis of functional requirements for the IOF.
The purpose of the proposed system is to provide a platform independent device (Intelligent Object)
management by utilization of set components. The functional requirements focus on deriving primary
functionality of server and client applications by description of required inputs, behaviours and outputs.
Systems variability modeling a textual model mixing class and feature conceptsijcsit
System’s reusability and cost are very important in software product line design area. Developers’ goal is
to increase system reusability and decreasing cost and efforts for building components from scratch for
each software configuration. This can be reached by developing software product line (SPL). To handle
SPL engineering process, several approaches with several techniques were developed. One of these
approaches is called separated approach. It requires separating the commonalities and variability for
system’s components to allow configuration selection based on user defined features. Textual notationbased
approaches have been used for their formal syntax and semantics to represent system features and
implementations. But these approaches are still weak in mixing features (conceptual level) and classes
(physical level) that guarantee smooth and automatic configuration generation for software releases. The
absence of methodology supporting the mixing process is a real weakness. In this paper, we enhanced
SPL’s reusability by introducing some meta-features, classified according to their functionalities. As a first
consequence, mixing class and feature concepts is supported in a simple way using class interfaces and
inherent features for smooth move from feature model to class model. And as a second consequence, the
mixing process is supported by a textual design and implementation methodology, mixing class and feature
models by combining their concepts in a single language. The supported configuration generation process
is simple, coherent, and complete.
A NEW IMAGE STEGANOGRAPHY ALGORITHM BASED ON MLSB METHOD WITH RANDOM PIXELS S...IJNSA Journal
In recent years, the rapid growth of information technology and digital communication has become very important to secure information transmission between the sender and receiver. Therefore, steganography introduces strongly to hide information and to communicate a secret data in an appropriate multimedia carrier, e.g., image, audio and video files. In this paper, a new algorithm for image steganography has been proposed to hide a large amount of secret data presented by secret color image. This algorithm is based on different size image segmentations (DSIS) and modified least significant bits (MLSB), where the DSIS algorithm has been applied to embed a secret image randomly instead of sequentially; this approach has been applied before embedding process. The number of bit to be replaced at each byte is non uniform, it bases on byte characteristics by constructing an effective hypothesis. The simulation results justify that the proposed approach is employed efficiently and satisfied high imperceptible with high payload capacity reached to four bits per byte.
encryption based lsb steganography technique for digital images and text dataINFOGAIN PUBLICATION
Digital steganography is the art and science of hiding communications; a steganographic system thus embeds secret data in public cover media so as not to arouse an eavesdropper’s suspicion. A steganographic system has two main aspects: steganographic capacity and imperceptibility. However, these two characteristics are at odds with each other. Furthermore, it is quite difficult to increase the steganographic capacity and simultaneously maintain the imperceptibility of a steganographic system. Additionally, there are still very limited methods of Steganography to be used with communication protocols, which represent unconventional but promising Steganography mediums. Digital image Steganography, as a method of secret communication, aims to convey a large amount of secret data, relatively to the size of cover image, between communicating parties. Additionally, it aims to avoid the suspicion of non-communicating parties to this kind of communication. Thus, this research addresses and proposes some methods to improve these fundamental aspects of digital image Steganography. Hence, some characteristics and properties of digital images have been employed to increase the steganographic capacity and enhance the stego image quality (imperceptibility). Here, the research aim is identified based on the established definition of the research problem and motivations. Unlike encryption, Steganography hides the very existence of secret information rather than hiding its meaning only. Image based Steganography is the most common system used since digital images are widely used over the Internet and Web. However, the capacity is mostly limited and restricted by the size of cover images. In addition, there is a tradeoff between both steganographic capacity and stego image quality. Therefore, increasing steganographic capacity and enhancing stego image quality are still challenges, and this is exactly our research main aim. To get a high steganographic capacity, novel Steganography methods were proposed. The first method was based on using 8x8 non-overlapping blocks and quantization table for DCT with compression. Second method incorporates the DWT technique, with quality of any stego images as enhanced to get correct hidden image. And last LSB as to store images with Key type security built in.
Developing Algorithms for Image Steganography and Increasing the Capacity Dep...IJCNCJournal
Steganography is a vital technique for transferring confidential information via an insecure network. In addition, digital images are used as a cover to communicate sensitive information. The Least Significant Bit (LSB) method is one of the simplest ways to insert secret data into a cover image. In this paper, the secret text is compressed twice by an Arithmetic coding algorithm, and the resulting secret bits are hidden in the cover pixels of the image corresponding to the pixels of each of the following three methods, one of three methods is used in each experiment: The first method, the edges of the image are modified to increase the number of edges, in the second method the lighter-colored regions are selected, and in the third method, the two methods are combined together to increase security and keep the secret message unrecognized. Hiding in each of the previous methods is done by using the LSB technique in the last 2-bit. The correction approach is used to increase the stego image's imperceptibility. The experimental results show that with an average message size of 29.8 kb, the average Peak Signal-to-Noise Ratio (PSNR) for the second proposed (Light regions) method equals 62.76 dB and for the third proposed (Edge and region) method equals 62.72 dB, which is a reasonable result when compared to other steganographic techniques.
DEVELOPING ALGORITHMS FOR IMAGE STEGANOGRAPHY AND INCREASING THE CAPACITY DEP...IJCNCJournal
Steganography is a vital technique for transferring confidential information via an insecure network. In
addition, digital images are used as a cover to communicate sensitive information. The Least Significant
Bit (LSB) method is one of the simplest ways to insert secret data into a cover image. In this paper, the
secret text is compressed twice by an Arithmetic coding algorithm, and the resulting secret bits are hidden
in the cover pixels of the image corresponding to the pixels of each of the following three methods, one of
three methods is used in each experiment: The first method, the edges of the image are modified to increase
the number of edges, in the second method the lighter-colored regions are selected, and in the third
method, the two methods are combined together to increase security and keep the secret message
unrecognized. Hiding in each of the previous methods is done by using the LSB technique in the last 2-bit.
The correction approach is used to increase the stego image's imperceptibility. The experimental results
show that with an average message size of 29.8 kb, the average Peak Signal-to-Noise Ratio (PSNR) for the
second proposed (Light regions) method equals 62.76 dB and for the third proposed (Edge and region)
method equals 62.72 dB, which is a reasonable result when compared to other steganographic techniques.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
We follow "Rigorous Publication" model - means that all articles appear on IJERD after full appraisal, effectiveness, legitimacy and reliability of research content. International Journal of Engineering Research and Development publishes papers online as well as provide hard copy of Journal to authors after publication of paper. It is intended to serve as a forum for researchers, practitioners and developers to exchange ideas and results for the advancement of Engineering & Technology.
A Survey of different Data Hiding Techniques in Digital Imagesijsrd.com
Steganography is the art and science of invisible communication, which hides the existence of the communicated message into media such as text, audio, image and video without any suspicion. Steganography is different from cryptography and watermarking in its objectives which includes undetectability, robustness (resistance to various image processing methods and compression) and capacity of the hidden data. Image Steganography uses digital image as its cover media. This paper analyzes and discusses various techniques available today for image steganography along with their strengths and weaknesses.
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.
EVALUATING THE PERFORMANCE OF THE SECURE BLOCK PERMUTATION IMAGE STEGANOGRAPH...IJNSA Journal
Recently, a new secure steganography algorithm has been proposed, namely, the secure Block Permutation Image Steganography (BPIS) algorithm. The new algorithm consists of five main steps, these are: convert the secret message to a binary sequence, divide the binary sequence into blocks, permute each block using a key-based randomly generated permutation, concatenate the permuted blocks forming a permuted binary sequence, and then utilize a plane-based Least-Significant-Bit (LSB) approach to embed the permuted binary sequence into BMP image file format. The performance of algorithm was given a preliminary evaluation through estimating the PSNR (Peak Signal-to-Noise Ratio) of the stego image for limited number of experiments comprised hiding text files of various sizes into BMP images. This paper presents a deeper algorithm performance evaluation; in particular, it evaluates the effects of length of permutation and occupation ratio on stego image quality and steganography processing time. Furthermore, it evaluates the algorithm performance for concealing different types of secret media, such as MS office file formats, image files, PDF files, executable files, and compressed files.
EVALUATING THE PERFORMANCE OF THE SECURE BLOCK PERMUTATION IMAGE STEGANOGRAPH...IJNSA Journal
Recently, a new secure steganography algorithm has been proposed, namely, the secure Block Permutation
Image Steganography (BPIS) algorithm. The new algorithm consists of five main steps, these are: convert
the secret message to a binary sequence, divide the binary sequence into blocks, permute each block using
a key-based randomly generated permutation, concatenate the permuted blocks forming a permuted binary
sequence, and then utilize a plane-based Least-Significant-Bit (LSB) approach to embed the permuted
binary sequence into BMP image file format. The performance of algorithm was given a preliminary
evaluation through estimating the PSNR (Peak Signal-to-Noise Ratio) of the stego image for limited
number of experiments comprised hiding text files of various sizes into BMP images. This paper presents a
deeper algorithm performance evaluation; in particular, it evaluates the effects of length of permutation
and occupation ratio on stego image quality and steganography processing time. Furthermore, it evaluates
the algorithm performance for concealing different types of secret media, such as MS office file formats,
image files, PDF files, executable files, and compressed files.
Comparative Study of Spatial Domain Image Steganography TechniquesEswar Publications
Steganography is an important area of research in information security. It is the technique of disclosing information into the cover image via. text, video, and image without causing statistically significant modification to the cover image. Secure communication of data through internet has become a main issue due to several passive and active attacks. The purpose of stegnography is to hide the existence of the message so that it becomes difficult for attacker to detect it. Different steganography techniques are implemented to hide the information effectively also researchers contributed various algorithms in each technique to improve the technique’s efficiency. In this paper we do a brief analysis of different spatial domain image stegnography techniques and their comparison. The modern secure image steganography presents a challenging task of transferring the embedded information to the destination without being detected.
In this paper, a new steganography algorithm has been suggested to enforce the security of data hiding and to increase the amount of payloads. This algorithm is based on four safety layers; the first safety layer has been initiated through compression and an encryption of a confidential message using a set partition in hierarchical trees (SPIHT) and advanced encryption standard (AES) mechanisms respectively. An irregular image segmentation algorithm (IIS) on a cover-image (Ic) has been constructed successfully in
the second safety layer, and it is based on the adaptive reallocation segments' edges (ARSE) by applying an
adaptive finite-element method (AFEM) to find the numerical solution of the proposed partial differential equation (PDE). An intelligent computing technique using a hybrid adaptive neural network with a modified ant colony optimizer (ANN_MACO) has been proposed in the third safety layer to construct a
learning system. This system accepts entry using support vector machine (SVM) to generate input patterns as features of byte attributes and produces new features to modify a cover-image. The significant innovation of the proposed novel steganography algorithm is applied efficiently on the forth
safety layer which is more robust for hiding a large amount of confidential message reach to six bits per pixel (bpp) into color images. The new approach of hiding algorithm works against statistical and visual attacks with high imperceptible of hiding data into stego-images (Is). The experimental results are
discussed and compared with the previous steganography algorithms; it demonstrates that the proposed algorithm has a significant improvement on the effect of the security level of steganography by making an arduous task of retrieving embedded confidential message from color images.
IMPROVED STEGANOGRAPHIC SECURITY BY APPLYING AN IRREGULAR IMAGE SEGMENTATION ...IJNSA Journal
In this paper, a new steganography algorithm has been suggested to enforce the security of data hiding and to increase the amount of payloads. This algorithm is based on four safety layers; the first safety layer has been initiated through compression and an encryption of a confidential message using a set partition in hierarchical trees (SPIHT) and advanced encryption standard (AES) mechanisms respectively. An irregular image segmentation algorithm (IIS) on a cover-image (Ic) has been constructed successfully in the second safety layer, and it is based on the adaptive reallocation segments' edges (ARSE) by applying an adaptive finite-element method (AFEM) to find the numerical solution of the proposed partial differential equation (PDE). An intelligent computing technique using a hybrid adaptive neural network with a modified ant colony optimizer (ANN_MACO) has been proposed in the third safety layer to construct a learning system. This system accepts entry using support vector machine (SVM) to generate input patterns as features of byte attributes and produces new features to modify a cover-image.
The significant innovation of the proposed novel steganography algorithm is applied efficiently on the forth safety layer which is more robust for hiding a large amount of confidential message reach to six bits per pixel (bpp) into color images. The new approach of hiding algorithm works against statistical and visual attacks with high imperceptible of hiding data into stego-images (Is). The experimental results are discussed and compared with the previous steganography algorithms; it demonstrates that the proposed algorithm has a significant improvement on the effect of the security level of steganography by making an arduous task of retrieving embedded confidential message from color images.
Design and Implementation of Data Hiding Technique by Using MPEG Video with C...Editor IJMTER
This paper proposes a technique on data hiding approaches using compressed MPEG video files.
This approach hides the message bits by modulating the quantization scale of constant bit rate MPEG
videos. Payload is calculated for each macroblock and proposes to achieve one message bit per
macroblock. Macroblock level feature variables are calculated.To find the association between
macroblock level feature variables and value of a hidden message bit, a Second Order Multivariate
regression model is used. To achieve the very high prediction accuracy, the regression model is used by
the decoder. To decode the message, a feature variable of MBs from the encoded bit stream are computed
by the decoder and expands them to the second order and uses the model weights to predict the message
bits. This solution provides very high precision accuracy in predicting the message bits . The proposed
technique is analyzed in term of quality distortion, excessive bit rate, message pay load and message
extraction accuracy. The proposed solution is better in terms of message payload while causing the less
distortion and reduced compression overheads compare to the previous works.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
ON THE IMAGE QUALITY AND ENCODING TIMES OF LSB, MSB AND COMBINED LSB-MSB
1. International Journal of Computer Science & Information Technology (IJCSIT) Vol 7, No 4, August 2015
DOI:10.5121/ijcsit.2015.7407 79
ON THE IMAGE QUALITY AND ENCODING TIMES
OF LSB, MSB AND COMBINED LSB-MSB
STEGANOGRAPHY ALGORITHMS USING DIGITAL
IMAGES
Solomon O.Akinola and Adebanke A.Olatidoye
Department of Computer Science, University of Ibadan, Nigeria
ABSTRACT
The Least Significant Bit (LSB) algorithm and the Most Significant Bit (MSB) algorithm are steganography
algorithms with each one having its demerits. This work therefore proposed a Hybrid approach and
compared its efficiency with LSB and MSB algorithms. The Least Significant Bit (LSB) and Most
Significant Bit (MSB) techniques were combined in the proposed algorithm. Two bits (the least significant
bit and the most significant bit) of the cover images were replaced with a secret message. Comparisons
were made based on Mean-Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and the encoding
time between the proposed algorithm, LSB and MSB after embedding in digital images. The combined
technique produced a stego-image with minimal distortion in image quality than MSB technique
independent of the nature of data that was hidden. However, LSB algorithm produced the best stego-image
quality. Large cover images however made the combined algorithm’s quality better improved. The
combined algorithm had lesser time of image and text encoding. Therefore, a trade-off exists between the
encoding time and the quality of stego-image as demonstrated in this work.
KEYWORDS
Steganography, Cover image, Most Significant Bit (LSB), Least Significant Bit (LSB).
1. INTRODUCTION
Steganography is the art and science of hiding sensitive information in ways that prevent
detection. The purpose of steganography is to convey a message in such a way that nobody apart
from the sender and intended recipient suspects the existence of the message. These messages are
transferred through cover carriers such as text, audio, images and protocols [1, 2]. The secret
message could be a plaintext, cipher text or images. The embedding of the message into a cover
object results in the production of a stego-image. Images are mostly used as cover objects in
steganography.
Different image Steganography technique exists which are classified into spatial domain and
transform domain steganography. In spatial domain scheme, the secret information is directly
embedded. Its high capability of hiding and easy retrieval makes it to be used frequently. An
example is the least significant bit algorithm which is key to the embedding algorithm proposed
in this paper.
Transform domain scheme is used for hiding a large amount of data. It hides information in
frequency domain by altering magnitude of all transforms of cover image. Discrete
Cosineransform (DCT), Discrete Fourier Transform, and Wavelet Transform are the main types
2. International Journal of Computer Science & Information Technology (IJCSIT) Vol 7, No 4, August 2015
80
of transforms used in steganography. These transforms all have coefficients associated with
them. The secret data is hidden within these coefficients which also defines how the image or file
should be transformed [3]. Examples include JPEG Steganography and Spread Spectrum.
The performance of a steganography technique can be measured using several parameters, among
which are imperceptibility, robustness and capacity. Imperceptibility is defined as the ability to
avoid detection, i.e. the inability to determine the existence of a hidden message. This makes it
an important requirement in steganography. Robustness refers to how well a steganography
technique can resist the extraction of hidden data. It measures the ability of the steganography
technique to survive the attempts of removing the hidden information. Such attempts include,
image manipulation (like cropping or rotating), data compression and image filtering [4]. Payload
Capacity represents the maximum amount of information that can be safely embedded and
retrieved in a work without being statistically detectable. When compared with watermarking
that requires embedding only a small amount of copyright information, Steganography requires
sufficient embedding capacity [5].
The Least Significant Bit (LSB) is one of most common embedding techniques. The least
significant bit is the least value in a binary number. In LSB algorithm, data is hidden in the least
significant bits of the cover image wfqhhich is not noticeable when viewed with the human eye
[4]. The most significant bit (also called the high-order bit) is the bit position in a binary number
having the greatest value.
The aim of this work is to compare the image quality and the encoding times of LSB, MSB and
the proposed Combined-LSB-MSB Steganography algorithms using digital images. The
objectives are to:
• Combine the LSB and MSB techniques into a Hybrid algorithm that embeds secret
message bits into the least significant bit and most significant bit of the cover image.
• Compare the LSB, MSB and the proposed algorithms (named Combined-LSB-MSB and
hence called Hybrid) in terms of encoding time, MSE (Mean Squared Error) and PSNR
(Peak Signal to Noise Ratio).
• Test the algorithms using different image formats (JPG and PNG) and the quality of image
with increase in file size.
The rest of the paper is organized as follows. Section II reviews existing image steganography
methods and section III presents the proposed image embedding method. The experimental
results & discussion are shown in section IV and conclusions are drawn in section V.
2. RELATED WORK
There has been several researches in hiding data inside an image using steganography technique.
In Warkentin et al. [6] proposed algorithm, the idea was to hide data inside the audiovisual files.
El-Emam’s [7] proposed steganography algorithm is based on hiding a large amount of data file
inside a coloured bitmap image. In his work, he filtered and segmented the image by using bits
replacement on the appropriate pixels. A concept defined by main cases with their sub cases for
each byte in one pixel was used to select these pixels randomly rather than sequentially. This
concept was both visual and statistical. The result of this concept was that 16 main cases with
their sub cases covered all aspects of the input data into color bitmap image. Three layers
provided high security which made it difficult to break through the encryption of the input data
and also undectable when steganalysis is applied. it was concluded that a large amount of data
that occupies 75% of the image size can be embedded efficiently and the output will be of high
quality.
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Chen et al. [8] modified a method proposed by Chang et al. [9] using the side match method. In
this method, data was hidden in the edge portions of the image. The image quality was improved
while maintaining the same embedding capacity because the human eyes could rarely see
differences in the edge portion. The embedding capacity can also be adjusted based on the
demands of individual users. In addition to the improvement on image quality, the proposed
approach provided respectable security as well. Wu and Tsai [10] proposed an algorithm using
pixel-value differencing which partioned the original image into non-overlapping blocks of two
consecutive pixels. A different value was calculated from the values of the two pixels in each
block. All possible different values were classified into a number of ranges. The human vision
sensitivity to gray value variations from smoothness to contrast was used in selecting the range
intervals. A new value which replaced the different value was used to embed the value of a sub-
stream of the secret message. The width of the range that the different value belongs to
determines the number of bits that can be embedded in a pixel pair. However, in this method the
modification is never out of the range interval. The result produced by this method is more
imperceptible than those yielded by simple least significant bit replacement method. The secret
message that was embedded can be extracted from the resulting stego-image without making
reference to the method of the original cover image. The security of the method was shown using
dual statistics attack.
Scott [11] work on steganographic techniques using digital images used several iterations of
replacement strategies during the construction of the application. The aim was to implement a
replacement and extraction steganography scheme using cover images. To extract the embedded
textual information from the image, the image created by the application must be processed. This
processing outputs the original message and some extra erroneous information. Comparism
between LSB replacement scheme with MSB replacement scheme asserted that MSB produced
noticeable differences to the cover during the most significant bit replacement. Rohit and Tarun
[12] compared LSB and MSB based steganography in gray-scale images. It was concluded that
the resulting stego-image using LSB shows no distortion when compared with the original image.
The performance of LSB was better than that of MSB. Kanzariya and Nimavat [4] compared
various image steganography techniques. The objectives were to identify the requirements of a
good steganography algorithm and to determine steganography techniques that are suitable for
different applications. In this work, some criteria for imperceptibility of an algorithm were
proposed.
3. THE PROPOSED METHOD
The proposed hybrid algorithm combines the LSB and MSB Steganography techniques. Two bits
(the least significant and the most significant bits) of the cover images were replaced with a
secret message. Figure 1 shows the framework of the proposed algorithm.
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Figure 1: Framework for the Proposed Hybrid-LSB-MSB Algorithm
From figure 1, once the cover image and the secret message (image or text) has been selected, the
embedding stage of the combined algorithm takes two bits of the secret message and embeds the
first message bit in the least significant bit of the cover image byte and the second message bit in
the most significant bit of the cover image byte. The output of this process is a stego-image. The
retrieving stage is just the inverse of the embedding stage.
A. Embedding Algorithm
Begin
Load the cover image
Convert image to byte array
Convert message data to byte array
If message cannot be contained in cover image
Exit with error message
Else
For each bit in the message byte
Begin
If LSB
Hide message bit in the lsb of the corresponding cover image byte
If MSB
Hide message bit in the msb of the corresponding cover image byte
If HYBRID
Get two message bits
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Hide the first message bit in the lsb of the corresponding cover image byte
Hide the second message bit in the msb of the corresponding cover image byte
End
End
B. Decoding Algorithm
Begin
Load stego image
Convert stego image into byte array
If decoding type is LSB
Begin
For the first 32 byte
Copy the lsb into an array of length 32
Convert the array into integer value
Create an array of length of the integer value
Starting from length 32+1 of the stego-
image array
Begin
Copy the lsb of the equivalent stego array into an array of length 8
Convert the array into a byte value and save in the corresponding index of the
created array
Convert the array value into string or image
End
End
The same approach goes for MSB and HYBRID
End
C. File Format
Any image file format can be used as both the cover image and the secret image. However, the
image was first converted into PNG format before anything can be done on it. After the whole
process, the image was converted back to its original format. PNG format is preferred because it
is supported by the Java image IO library; it applies lossless file compression method and allows
for easy interchange and viewing of image data stored on local or remote computer systems [13].
Also, it seems to maintain a high degree of image quality after the message has been embedded
[11].
D. Comparison Procedures
To compare the image quality of the three algorithms i.e. the LSB, MSB and the proposed
Hybrid algorithm, three metrics were used, which are the Mean-Squared Error (MSE), the Peak
Signal-to-Noise Ratio (PSNR) and the encoding time.
• Mean-Squared Error (MSE)
The MSE represents the cumulative squared error between the cover image and the stego-image.
To calculate the mean-squared error (MSE) between two images I1 (M, N) and I2 (M, N) the
equation is as follows:
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M and N are the number of rows and columns in the input images respectively [14].
• Peak Signal-to-Noise Ratio [PSNR]
The PSNR measures the statistical difference between the cover and stego image [15]. The mean-
squared error value is needed to compute the PSNR. The equation is as follows:
The value of R is 255.
However, the lower the MSE value and the higher the PSNR value then the better the quality of
the image.
4. RESULTS AND DISCUSSION
A simple system was developed to implement the LSB, MSB and the proposed combined
algorithms using JAVA programming language. There are two sides to the system, the encoding
interface and the decoding interface for hiding and retrieving purposes respectively.
We tested the system using two different image formats (roses.jpg, giraffe.png) as cover images.
A blue-footed booby bird (Figure 2) with dimension 160 x 120 pixels and file size of 4 kilo byte
was used as the message image for each cover image respectively. A 30.4 kilo byte document
was also used as message text.
Figure 2: Secret Image
In order to evaluate the performance of the proposed method, stego-images from the LSB, MSB
and the proposed Hybrid method were compared using MSE, PSNR and encoding time metrics
The methods were also tested with increased sizes of the images. Figures 3a, 3b, 4a and 4b show
the differences between the Least Significant Bit (LSB), Most Significant Bit (MSB) and the
combined algorithm after embedding messages in them.
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Figure 3a (560 x 448 pixels rose.jpg hiding an image): (I) Original image (II) Stego-image using LSB
Figure 3a (560 x 448 pixels rose.jpg hiding an image): (III) Stego-image using MSB (IV) Stego-image
using Combined LSB-MSB
Using roses.jpg with dimension 560 x 448 pixels as cover image and the blue-footed booby bird
image as message, it can be seen from image II of figure 3a that there are no noticeable
differences between the original cover image and the resultant image after hiding in the Least
Significant Bit. Images 3a (III) and 3a (IV) show noticeable differences when compared to the
original cover image using Most Significant Bit and combined LSB-MSB algorithms
respectively. However, MSB (3a III) shows much difference.
Increasing the dimension of roses.jpg to 5040 x 4032 pixels, the payload capacity increases for
MSB and proposed algorithm (figure 3b (III & IV). Therefore, the larger the cover image the
more data that can be stored.
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Figure 3b (5040 x 4032 pixels rose.jpg hiding an image): (I) Original image (II) Stego-image using LSB
Combined LSB-MSB
Figure 3b (5040 x 4032 pixels rose.jpg hiding an image): (III) Stego-image using MSB (IV) Stego-image
using Combined LSB-MSB
Figure 4a shows the output of the newly created stego-images after hiding text with a file size of
30.4kb (31,160 bytes) in an image in PNG format. The dimension of the cover image, giraffe.png
is 750 x 1125 pixels. Image 4a (II) showed no noticeable difference when compared to the
original cover image after embedding text using LSB algorithm. The differences are noticeable at
the top sections of Figures 4a III and IV for MSB and the combined algorithms respectively.
Figure 4a (750 x 1125 pixels giraffe.png hiding text): (I) Original image (II) Stego-image using LSB
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Figure 4a (750 x 1125 pixels giraffe.png hiding text): (III) Stego-image using MSB (IV) Stego-image using
Combined LSB-MSB
Increasing the dimension of the PNG file to 6750 x 10125 pixels produced a stego-image
indistinguishable from the original cover image when viewed with the human eyes for the three
algorithms (Figure 4b).
Figure 4b (6750 x 10125 pixels giraffe.png hiding text): (I) Original image (II) Stego-image using LSB
Figure 4b (6750 x 10125 pixels giraffe.png hiding text): (III) Stego-image using MSB (IV) Stego-image
using Combined LSB-MSB
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5. HELPFUL HINTS
Table 1 shows the MSE, PSNR and encoding times of the cover images for image and text
embedding. It can be seen that a lower MSE value and a higher PSNR value for LSB algorithm
as compared to the MSB and proposed Hybrid algorithms for both image and text were obtained.
This results into a better image quality since the lower the MSE value and the higher the PSNR
value, the better the quality of the image and hence imperceptibility is improved.
Although the embedding capacity of the proposed method (Hybrid) is low compared to LSB, the
proposed method gives better performance in all the parameters than MSB. The stego-image
generated after embedding the secret message in the cover image is almost identical to the
original image. However, when the sizes of the cover images were increased, the image quality
of the proposed algorithm increased, which means that the larger the cover image, the better the
hiding capacity. Also, the encoding times of the proposed Hybrid algorithm for various sizes of
the different images were lesser compared to other methods.
Table 1: Values of Encoding Time, MSEs and PSNRs of stego-images in which image and text is embedded
respectively.
Figures 5a and 5b shows the bar chart of results obtained with rose.jpg of sizes 560 x 448 and
5040 x 4032 pixels after embedding an image using LSB, MSB and Hybrid algorithms
respectively. The LSB algorithm had the lowest MSE and highest PSNR values while the
proposed combined algorithm had the lowest encoding time.
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Figure 5a: The Encoding Time (ms), MSE (dB) and PSNR (dB) of 560 x 448 pixels rose.jpg
Figure 5b: The Encoding Time (ms), MSE (dB) and PSNR (dB) of 5040 x 4032 pixels rose.jpg
Figures 6a and 6b shows the bar chart of results obtained with giraffe.png of sizes 750 x 1125
and 6750 x 10125 pixels after embedding text using LSB, MSB and com algorithms respectively.
The LSB algorithm also had the lowest MSE value and the highest PSNR value while the
proposed Hybrid algorithm had the lowest encoding time value.
Figure 6a: The Encoding Time (ms), MSE (dB) and PSNR (dB) of 750 x 1125 pixels giraffe.png
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Figure 6b: The Encoding Time (ms), MSE (dB) and PSNR (dB) of 6750 x 10125 pixels giraffe.png
Overall, LSB gives a best performance in terms of MSE and PSNR than the MSB and the
proposed Hybrid algorithm while the proposed Hybrid algorithm gives the best performance in
terms of the encoding time and better than MSB. The result obtained in this work confirms the
submission of Rohit and Tarun [12] that LSB steganography is much better than MSB
steganography for hiding messages. Scott [11] paper also compared LSB replacement scheme
with MSB replacement scheme and asserted that MSB produced noticeable differences to the
cover during the most significant bit replacement.
6. CONCLUSION
In this work, a Hybrid (LSB-MSB) algorithm was developed for embedding images and text into
images. The Hybrid algorithm suggests the embedding of secret message bits into the least
significant bit and the most significant bit of the cover image. The performance measure of
image quality due to embedding for LSB, MSB and the proposed Hybrid technique was
evaluated based on three error metrics; Mean-Squared Error (MSE), Peak Signal-to-Noise Ratio
(PSNR) and the time it takes each algorithm to embed a message in a cover image. The results
presented and analyzed show that the stego-images of LSB have the highest PSNR and the lowest
MSE values, making it very efficient to hide the data inside the image. However, based on the
encoding time, the combined LSB-MSB algorithm takes lesser time in embedding than LSB and
MSB.
Conclusively, LSB algorithm gives a better performance than the combined LSB-MSB algorithm
but a larger file size of the cover image makes the combined algorithm produces images with
good quality. Nevertheless, the proposed Hybrid algorithm produced better image quality than
MSB algorithm.
In the future work, the security of using the hybrid algorithm could be improved by working on
the compression ratio for stronger embedding procedures and also the use of the proposed
combined LSB-MSB algorithm on large sized gray-scale images.
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Authors
Akinola Olalekan is a Senior lecturer of Computer Science at the University of Ibadan,
Nigeria. He had his PhD Degree in Software Engineering from the same University in
Nigeria. His research focus is on software quality assurance techniques.
Adebanke Olatidoye had her Masters Degree in Computer Science from University of
Ibadan, Nigeria. She also had her first Degree in Computer Science from Ladoke Akintola
University of Technology, Ogbomoso, Nigeria.