To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
JPM1404 Designing an Efficient Image Encryption-Then-Compression System via...chennaijp
JP INFOTECH is one of the leading Matlab projects provider in Chennai having experience faculties. We have list of image processing projects as our own and also we can make projects based on your own base paper concept also.
For more details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/matlab-projects/
DATA HIDING IN ENCRYPTED H.264 VIDEO FORMATalphin jose
I-frames, P-frames, and B-frames are the three major picture types or frame types used in video compression algorithms. I-frames are fully specified frames that do not require other frames to decode but are the least compressible. P-frames store only the changes from previous frames and are more compressible than I-frames but require previous frames to decode. B-frames can use both previous and forward frames for reference and achieve the highest compression but require both previous and forward frames to decode. I-frames are used as random access points and references for decoding other frames.
Image secret sharing using Shamir's scheme with Steganography2510stk
This document discusses using Shamir's secret sharing algorithm and steganography to securely share secret images. The objectives are to provide more security for image communication while achieving transparency and preventing tampering. Shamir's algorithm is used to split images into shares, and steganography techniques like LSB encoding are used to hide the shares in cover images. This allows the shares to be transmitted securely without drawing attention. Potential applications include secure medical image sharing and military photography. The document reviews relevant literature and provides an example of a secret image being split and hidden in stego images. Future work could improve reconstruction quality and use additional cryptography techniques for enhanced security.
Designing an efficient image encryption then-compression system via predictio...LeMeniz Infotech
The document proposes a new image encryption-then-compression system that aims to efficiently compress encrypted images while maintaining a high level of security. It suggests encrypting images in the prediction error domain and using context-adaptive arithmetic coding to compress the encrypted data, resulting in only a negligible loss in compression efficiency compared to compressing the original images. This approach improves upon existing systems that induce significant penalties on compression performance when encrypting images prior to compression.
The document discusses image steganography techniques. It begins by defining steganography as concealed writing and distinguishing it from cryptography. It then describes the basic process of embedding a secret message into a cover image to produce a stego-image. Different embedding algorithms are presented, including Least Significant Bit substitution and LSB with randomization. Histograms are used to analyze the differences between cover and stego-images. The document concludes by discussing attackers and techniques to improve robustness, such as LSB matching and Mielikainen's improved LSB matching method.
DIP Using Image Encryption and XOR Operation Affine Transformiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
JPM1404 Designing an Efficient Image Encryption-Then-Compression System via...chennaijp
JP INFOTECH is one of the leading Matlab projects provider in Chennai having experience faculties. We have list of image processing projects as our own and also we can make projects based on your own base paper concept also.
For more details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/matlab-projects/
DATA HIDING IN ENCRYPTED H.264 VIDEO FORMATalphin jose
I-frames, P-frames, and B-frames are the three major picture types or frame types used in video compression algorithms. I-frames are fully specified frames that do not require other frames to decode but are the least compressible. P-frames store only the changes from previous frames and are more compressible than I-frames but require previous frames to decode. B-frames can use both previous and forward frames for reference and achieve the highest compression but require both previous and forward frames to decode. I-frames are used as random access points and references for decoding other frames.
Image secret sharing using Shamir's scheme with Steganography2510stk
This document discusses using Shamir's secret sharing algorithm and steganography to securely share secret images. The objectives are to provide more security for image communication while achieving transparency and preventing tampering. Shamir's algorithm is used to split images into shares, and steganography techniques like LSB encoding are used to hide the shares in cover images. This allows the shares to be transmitted securely without drawing attention. Potential applications include secure medical image sharing and military photography. The document reviews relevant literature and provides an example of a secret image being split and hidden in stego images. Future work could improve reconstruction quality and use additional cryptography techniques for enhanced security.
Designing an efficient image encryption then-compression system via predictio...LeMeniz Infotech
The document proposes a new image encryption-then-compression system that aims to efficiently compress encrypted images while maintaining a high level of security. It suggests encrypting images in the prediction error domain and using context-adaptive arithmetic coding to compress the encrypted data, resulting in only a negligible loss in compression efficiency compared to compressing the original images. This approach improves upon existing systems that induce significant penalties on compression performance when encrypting images prior to compression.
The document discusses image steganography techniques. It begins by defining steganography as concealed writing and distinguishing it from cryptography. It then describes the basic process of embedding a secret message into a cover image to produce a stego-image. Different embedding algorithms are presented, including Least Significant Bit substitution and LSB with randomization. Histograms are used to analyze the differences between cover and stego-images. The document concludes by discussing attackers and techniques to improve robustness, such as LSB matching and Mielikainen's improved LSB matching method.
DIP Using Image Encryption and XOR Operation Affine Transformiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Secured Reversible Data Hiding In Encrypted Images Using Hyper ChaosCSCJournals
Recently, more and more attention is paid to reversible data hiding (RDH) in encrypted images, since it maintains the excellent property that the original cover can be losslessly recovered after embedded data is extracted while protecting the image content’s confidentiality. All previous methods embed data by reversibly vacating room from the encrypted images, which may be subject to some errors on data extraction and/or image restoration. Here a novel method is proposed by reserving room before encryption with a traditional RDH algorithm, and thus it is easy for the data hider to reversibly embed data in the encrypted image. Moreover data to be embedded is shuffled using a hyper chaotic function which is difficult to be extracted from the stego image without original key. A digital water mark is also embedded which ensures integrity of the data. The proposed method has been validated against three other available RDH schemes and it is observed that the proposed scheme outperforms these RDH schemes both in visual quality and payload. The proposed method can achieve real reversibility, that is, data extraction and image recovery are free of any error.
Reversible data hiding in encrypted images by reserving room before encryptionIEEEFINALYEARPROJECTS
The document proposes a novel reversible data hiding method called "reserving room before encryption" (RRBE). It reserves room in the original image prior to encryption using a traditional reversible data hiding algorithm. This allows easy embedding of data in the encrypted image without errors during extraction and recovery. Experiments show it can embed over 10 times more payload than previous methods like vacating room from encrypted images, for the same image quality. The key advantages are real reversibility without extraction or recovery errors, and improved image quality for a given payload or increased payload for acceptable quality.
Reversible Data Hiding in Encrypted Image: A ReviewEditor IJMTER
Recently, more and more attention is paid to reversible data hiding (RDH) in encrypted
images, since it maintains the excellent property that the original cover can be losslessly recovered
after embedded data is extracted while protecting the image content’s confidentiality. All previous
methods embed data by reversibly vacating room from the encrypted images, which may be subject
to some errors on data extraction and/or image restoration. In this survey paper, we discuss about
various methods and algorithms which were used for reversible data hiding (RDH) in encrypted
image to make data hiding process effortless. We also use visual cryptographic approach for
encryption which helps to protect the image during transmission. The scheme is suitable for
authentication based application where collective acceptance and decision making plays an important
role. The main goal is to retrieve the original image with lossless process and minimum computation
during image encryption /decryption by using keyless approach.
Encryption converts plaintext into ciphertext using an algorithm and key. Gaussian elimination with partial pivoting and row exchange is used to encrypt images by converting the image matrix to an upper triangular matrix and generating a decryption key. The encrypted image matrix and key can then be multiplied to recover the original image matrix and decrypt the image. This algorithm allows for faster encryption time while still producing robust encryption to prevent unauthorized access to images.
The document proposes a chaotic image encryption technique using Henon chaotic systems. It consists of two main steps: 1) Image fusion between the original image and a key image. 2) Encrypting the pixel values of the fused image using a Henon chaotic map. The technique aims to provide high security with less computational time compared to traditional encryption methods. Experimental results show the algorithm is sensitive to keys and resistant to brute force attacks. The technique can be used for applications like secure internet image transmission.
This document discusses image encryption using a chaotic artificial neural network. It begins by introducing image encryption and its importance for securely transmitting valuable data over the internet. It then provides background on encryption techniques and discusses how image encryption works. The document outlines chaotic cryptography and why characteristics of chaos make it suitable for cryptography. It also discusses artificial neural networks and how they can be used for image encryption. In particular, it describes using a feedforward neural network with hidden layers to encrypt images.
EMPIRICAL STUDY OF ALGORITHMS AND TECHNIQUES IN VIDEO STEGANOGRAPHYJournal For Research
Steganography is the art and science of hiding the actual important information under graphics, text, cover file etc. These techniques may be applied without fear of image destruction because they are more integrated into the image. Information can be in the form of text, audio, video. The purpose of steganography is to covert communication and to hide a message from a third party or intruder. Steganography is often confused with cryptography because the two are similar in the way that both are used to protect confidential information. Though there are many types of steganography, video Steganography is more reliable due to high capacity image, more data embedment, perceptual redundancy etc. This research paper deals with various Video Steganography techniques and algorithms including Spatial Domain, Pseudorandom permutations, TPVD (Tri-way pixel value differencing), Motion Vector Technique, Video Compression, and Motion Vector Technique. The Video compression which uses modern coding techniques to reduce redundancy in video data has been also studied and analyzed. In fact, Video compression operates on square-shaped groups or blocks of neighboring pixels, often called macro blocks. These pixel groups or blocks of pixels are compared from one frame to the next and the video compression code sends only the differences within those blocks. Generally, the motion field in video compression is assumed to be translational with horizontal component and vertical component and denoted in vector form for the spatial variables in the underlying image, such as three steps search, etc. The study also discusses and focusses on the evolution of the Video Steganography techniques and algorithms over the years based on its application and subsequent merits and demerits. Further, Advanced Video Steganography Algorithm/Bit Exchange Method based on the bit shifting and XOR operation in the secret message file has been studied and implemented. The encrypted secret message is embed in the cover file in alternate byte. The bits are substituted in LSB & LSB+3 bits in the cover file. Finally, the simulation and evaluation of the above mentioned approach is performed using MATLAB tools.
This document reviews various video steganography methods that use neural networks. It discusses how neural networks can be used for steganalysis to detect hidden data in digital media. The document provides an overview of different neural network approaches that have been used for video watermarking and audio digital watermarking. These include using neural networks to preferentially allocate watermarks to motion coefficients in video and memorizing watermarks in the neurons of a counterpropagation neural network for audio. The conclusion states that neural network techniques can help improve the performance of various video steganography methods.
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.
Lossless and reversible data hiding in encrypted images with public key crypt...LogicMindtech Nologies
IMAGE PROCESSING Projects for M. Tech, IMAGE PROCESSING Projects in Vijayanagar, IMAGE PROCESSING Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, IMAGE PROCESSING IEEE projects in Bangalore, IEEE 2015 IMAGE PROCESSING Projects, MATLAB Image Processing Projects, MATLAB Image Processing Projects in Bangalore, MATLAB Image Processing Projects in Vijayangar
IRJET-Data Embedding Method using Adaptive Pixel Pair Matching AlgorithmIRJET Journal
This document summarizes a research paper that proposes a new data embedding technique called adaptive pixel pair matching (APPM) for digital image steganography. The APPM technique hides secret data by replacing pairs of pixels in the cover image with coordinates that represent the hidden data. This allows data to be hidden in any numerical system. The document outlines existing steganography techniques including least significant bit replacement and transform domain methods. It then describes the proposed APPM technique in more detail, asserting it offers lower distortion than other methods by providing more compact pixel neighborhoods and flexible numerical representation of hidden data.
Reversible Data Hiding in Encrypted color images by Reserving Room before Enc...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Lossless and reversible data hiding in encrypted images with public key crypt...LeMeniz Infotech
Lossless and reversible data hiding in encrypted images with public key cryptography
Do Your Projects With Technology Experts
To Get this projects Call : 9566355386 / 99625 88976
Web : http://www.lemenizinfotech.com
Web : http://www.ieeemaster.com
Mail : projects@lemenizinfotech.com
Blog : http://ieeeprojectspondicherry.weebly.com
Blog : http://www.ieeeprojectsinpondicherry.blogspot.in/
Youtube:https://www.youtube.com/watch?v=eesBNUnKvws
Reversible Multiple Image Secret Sharing using Discrete Haar Wavelet Transform IJECEIAES
Multiple Secret Image Sharing scheme is a protected approach to transmit more than one secret image over a communication channel. Conventionally, only single secret image is shared over a channel at a time. But as technology grew up, there is a need to share more than one secret image. A fast (r, n) multiple secret image sharing scheme based on discrete haar wavelet transform has been proposed to encrypt m secret images into n noisy images that are stored over different servers. To recover m secret images r noise images are required. Haar Discrete Wavelet Transform (DWT) is employed as reduction process of each secret image to its quarter size (i.e., LL subband). The LL subbands for all secrets have been combined in one secret that will be split later into r subblocks randomly using proposed high pseudo random generator. Finally, a developed (r, n) threshold multiple image secret sharing based one linear system has been used to generate unrelated shares. The experimental results showed that the generated shares are more secure and unrelated. The size reductions of generated shares were 1:4r of the size of each of original image. Also, the randomness test shows a good degree of randomness and security.
A secure image steganography based on burrows wheeler transform and dynamic b...IJECEIAES
In modern public communication networks, digital data is massively transmitted through the internet with a high risk of data piracy. Steganography is a technique used to transmit data without arousing suspicion of secret data existence. In this paper, a color image steganography technique is proposed in spatial domain. The cover image is segmented into non-overlapping blocks which are scattered among image size window using Burrows Wheeler transform before embedding. Secret data is embedded in each block according to its sequence in the Burrows Wheeler transform output. The hiding method is an operation of an exclusive-or between a virtual bit which is generated from the most significant bit and the least significant bits of the cover pixel. Results of the algorithm are analyzed according to its degradation of the output image and embedding capacity. The results are also compared with other existing methods.
This document proposes a method called learnable image encryption that allows deep learning to be performed on encrypted images while protecting privacy. It works by applying weak block-wise encryption to images before training deep learning models. The models can still learn meaningful patterns from the encrypted images. This approach could help shopping malls analyze customer behavior from security camera footage or allow companies to develop AI systems using encrypted data without compromising privacy. The method achieves comparable accuracy to training on plain images while keeping the encrypted images unintelligible to humans. Code and details on the block-wise encryption and decryption algorithms are available online.
The document provides an introduction to image encryption using AES key expansion. It discusses how traditional encryption techniques are not well-suited for encrypting large multimedia files like images due to their size and characteristics. The objective of the study is to develop an image encryption system that is computationally secure, fast enough for real-time use, and widely acceptable. It reviews related works in image encryption and discusses limitations of only using a 128-bit AES key. The document is organized into chapters covering cryptography fundamentals, image cryptosystems, AES algorithm details, an example of AES key expansion, and experimental analysis.
This document discusses steganography and image steganography techniques. It defines steganography as hiding information within other information to avoid detection. Image steganography is described as hiding data in digital images using techniques like least significant bit encoding. The document outlines the LSB algorithm, which replaces the least significant bits of image pixel values with bits of the hidden message. Examples are given to illustrate how short messages can be concealed in an image using this method.
A Secure Data Communication System Using Cryptography and SteganographyIJCNCJournal
The information security has become one of the most significant problems in data communication. So it
becomes an inseparable part of data communication. In order to address this problem, cryptography and
steganography can be combined. This paper proposes a secure communication system. It employs
cryptographic algorithm together with steganography. The jointing of these techniques provides a robust
and strong communication system that able to withstand against attackers. In this paper, the filter bank
cipher is used to encrypt the secret text message, it provide high level of security, scalability and speed.
After that, a discrete wavelet transforms (DWT) based steganography is employed to hide the encrypted
message in the cover image by modifying the wavelet coefficients. The performance of the proposed system
is evaluated using peak signal to noise ratio (PSNR) and histogram analysis. The simulation results show
that, the proposed system provides high level of security.
A SECURE DATA COMMUNICATION SYSTEM USING CRYPTOGRAPHY AND STEGANOGRAPHY IJCNCJournal
The information security has become one of the most significant problems in data communication. So it
becomes an inseparable part of data communication. In order to address this problem, cryptography and
steganography can be combined. This paper proposes a secure communication system. It employs
cryptographic algorithm together with steganography. The jointing of these techniques provides a robust
and strong communication system that able to withstand against attackers. In this paper, the filter bank
cipher is used to encrypt the secret text message, it provide high level of security, scalability and speed.
After that, a discrete wavelet transforms (DWT) based steganography is employed to hide the encrypted
message in the cover image by modifying the wavelet coefficients. The performance of the proposed system
is evaluated using peak signal to noise ratio (PSNR) and histogram analysis. The simulation results show
that, the proposed system provides high level of security.
Secured Reversible Data Hiding In Encrypted Images Using Hyper ChaosCSCJournals
Recently, more and more attention is paid to reversible data hiding (RDH) in encrypted images, since it maintains the excellent property that the original cover can be losslessly recovered after embedded data is extracted while protecting the image content’s confidentiality. All previous methods embed data by reversibly vacating room from the encrypted images, which may be subject to some errors on data extraction and/or image restoration. Here a novel method is proposed by reserving room before encryption with a traditional RDH algorithm, and thus it is easy for the data hider to reversibly embed data in the encrypted image. Moreover data to be embedded is shuffled using a hyper chaotic function which is difficult to be extracted from the stego image without original key. A digital water mark is also embedded which ensures integrity of the data. The proposed method has been validated against three other available RDH schemes and it is observed that the proposed scheme outperforms these RDH schemes both in visual quality and payload. The proposed method can achieve real reversibility, that is, data extraction and image recovery are free of any error.
Reversible data hiding in encrypted images by reserving room before encryptionIEEEFINALYEARPROJECTS
The document proposes a novel reversible data hiding method called "reserving room before encryption" (RRBE). It reserves room in the original image prior to encryption using a traditional reversible data hiding algorithm. This allows easy embedding of data in the encrypted image without errors during extraction and recovery. Experiments show it can embed over 10 times more payload than previous methods like vacating room from encrypted images, for the same image quality. The key advantages are real reversibility without extraction or recovery errors, and improved image quality for a given payload or increased payload for acceptable quality.
Reversible Data Hiding in Encrypted Image: A ReviewEditor IJMTER
Recently, more and more attention is paid to reversible data hiding (RDH) in encrypted
images, since it maintains the excellent property that the original cover can be losslessly recovered
after embedded data is extracted while protecting the image content’s confidentiality. All previous
methods embed data by reversibly vacating room from the encrypted images, which may be subject
to some errors on data extraction and/or image restoration. In this survey paper, we discuss about
various methods and algorithms which were used for reversible data hiding (RDH) in encrypted
image to make data hiding process effortless. We also use visual cryptographic approach for
encryption which helps to protect the image during transmission. The scheme is suitable for
authentication based application where collective acceptance and decision making plays an important
role. The main goal is to retrieve the original image with lossless process and minimum computation
during image encryption /decryption by using keyless approach.
Encryption converts plaintext into ciphertext using an algorithm and key. Gaussian elimination with partial pivoting and row exchange is used to encrypt images by converting the image matrix to an upper triangular matrix and generating a decryption key. The encrypted image matrix and key can then be multiplied to recover the original image matrix and decrypt the image. This algorithm allows for faster encryption time while still producing robust encryption to prevent unauthorized access to images.
The document proposes a chaotic image encryption technique using Henon chaotic systems. It consists of two main steps: 1) Image fusion between the original image and a key image. 2) Encrypting the pixel values of the fused image using a Henon chaotic map. The technique aims to provide high security with less computational time compared to traditional encryption methods. Experimental results show the algorithm is sensitive to keys and resistant to brute force attacks. The technique can be used for applications like secure internet image transmission.
This document discusses image encryption using a chaotic artificial neural network. It begins by introducing image encryption and its importance for securely transmitting valuable data over the internet. It then provides background on encryption techniques and discusses how image encryption works. The document outlines chaotic cryptography and why characteristics of chaos make it suitable for cryptography. It also discusses artificial neural networks and how they can be used for image encryption. In particular, it describes using a feedforward neural network with hidden layers to encrypt images.
EMPIRICAL STUDY OF ALGORITHMS AND TECHNIQUES IN VIDEO STEGANOGRAPHYJournal For Research
Steganography is the art and science of hiding the actual important information under graphics, text, cover file etc. These techniques may be applied without fear of image destruction because they are more integrated into the image. Information can be in the form of text, audio, video. The purpose of steganography is to covert communication and to hide a message from a third party or intruder. Steganography is often confused with cryptography because the two are similar in the way that both are used to protect confidential information. Though there are many types of steganography, video Steganography is more reliable due to high capacity image, more data embedment, perceptual redundancy etc. This research paper deals with various Video Steganography techniques and algorithms including Spatial Domain, Pseudorandom permutations, TPVD (Tri-way pixel value differencing), Motion Vector Technique, Video Compression, and Motion Vector Technique. The Video compression which uses modern coding techniques to reduce redundancy in video data has been also studied and analyzed. In fact, Video compression operates on square-shaped groups or blocks of neighboring pixels, often called macro blocks. These pixel groups or blocks of pixels are compared from one frame to the next and the video compression code sends only the differences within those blocks. Generally, the motion field in video compression is assumed to be translational with horizontal component and vertical component and denoted in vector form for the spatial variables in the underlying image, such as three steps search, etc. The study also discusses and focusses on the evolution of the Video Steganography techniques and algorithms over the years based on its application and subsequent merits and demerits. Further, Advanced Video Steganography Algorithm/Bit Exchange Method based on the bit shifting and XOR operation in the secret message file has been studied and implemented. The encrypted secret message is embed in the cover file in alternate byte. The bits are substituted in LSB & LSB+3 bits in the cover file. Finally, the simulation and evaluation of the above mentioned approach is performed using MATLAB tools.
This document reviews various video steganography methods that use neural networks. It discusses how neural networks can be used for steganalysis to detect hidden data in digital media. The document provides an overview of different neural network approaches that have been used for video watermarking and audio digital watermarking. These include using neural networks to preferentially allocate watermarks to motion coefficients in video and memorizing watermarks in the neurons of a counterpropagation neural network for audio. The conclusion states that neural network techniques can help improve the performance of various video steganography methods.
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.
Lossless and reversible data hiding in encrypted images with public key crypt...LogicMindtech Nologies
IMAGE PROCESSING Projects for M. Tech, IMAGE PROCESSING Projects in Vijayanagar, IMAGE PROCESSING Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, IMAGE PROCESSING IEEE projects in Bangalore, IEEE 2015 IMAGE PROCESSING Projects, MATLAB Image Processing Projects, MATLAB Image Processing Projects in Bangalore, MATLAB Image Processing Projects in Vijayangar
IRJET-Data Embedding Method using Adaptive Pixel Pair Matching AlgorithmIRJET Journal
This document summarizes a research paper that proposes a new data embedding technique called adaptive pixel pair matching (APPM) for digital image steganography. The APPM technique hides secret data by replacing pairs of pixels in the cover image with coordinates that represent the hidden data. This allows data to be hidden in any numerical system. The document outlines existing steganography techniques including least significant bit replacement and transform domain methods. It then describes the proposed APPM technique in more detail, asserting it offers lower distortion than other methods by providing more compact pixel neighborhoods and flexible numerical representation of hidden data.
Reversible Data Hiding in Encrypted color images by Reserving Room before Enc...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Lossless and reversible data hiding in encrypted images with public key crypt...LeMeniz Infotech
Lossless and reversible data hiding in encrypted images with public key cryptography
Do Your Projects With Technology Experts
To Get this projects Call : 9566355386 / 99625 88976
Web : http://www.lemenizinfotech.com
Web : http://www.ieeemaster.com
Mail : projects@lemenizinfotech.com
Blog : http://ieeeprojectspondicherry.weebly.com
Blog : http://www.ieeeprojectsinpondicherry.blogspot.in/
Youtube:https://www.youtube.com/watch?v=eesBNUnKvws
Reversible Multiple Image Secret Sharing using Discrete Haar Wavelet Transform IJECEIAES
Multiple Secret Image Sharing scheme is a protected approach to transmit more than one secret image over a communication channel. Conventionally, only single secret image is shared over a channel at a time. But as technology grew up, there is a need to share more than one secret image. A fast (r, n) multiple secret image sharing scheme based on discrete haar wavelet transform has been proposed to encrypt m secret images into n noisy images that are stored over different servers. To recover m secret images r noise images are required. Haar Discrete Wavelet Transform (DWT) is employed as reduction process of each secret image to its quarter size (i.e., LL subband). The LL subbands for all secrets have been combined in one secret that will be split later into r subblocks randomly using proposed high pseudo random generator. Finally, a developed (r, n) threshold multiple image secret sharing based one linear system has been used to generate unrelated shares. The experimental results showed that the generated shares are more secure and unrelated. The size reductions of generated shares were 1:4r of the size of each of original image. Also, the randomness test shows a good degree of randomness and security.
A secure image steganography based on burrows wheeler transform and dynamic b...IJECEIAES
In modern public communication networks, digital data is massively transmitted through the internet with a high risk of data piracy. Steganography is a technique used to transmit data without arousing suspicion of secret data existence. In this paper, a color image steganography technique is proposed in spatial domain. The cover image is segmented into non-overlapping blocks which are scattered among image size window using Burrows Wheeler transform before embedding. Secret data is embedded in each block according to its sequence in the Burrows Wheeler transform output. The hiding method is an operation of an exclusive-or between a virtual bit which is generated from the most significant bit and the least significant bits of the cover pixel. Results of the algorithm are analyzed according to its degradation of the output image and embedding capacity. The results are also compared with other existing methods.
This document proposes a method called learnable image encryption that allows deep learning to be performed on encrypted images while protecting privacy. It works by applying weak block-wise encryption to images before training deep learning models. The models can still learn meaningful patterns from the encrypted images. This approach could help shopping malls analyze customer behavior from security camera footage or allow companies to develop AI systems using encrypted data without compromising privacy. The method achieves comparable accuracy to training on plain images while keeping the encrypted images unintelligible to humans. Code and details on the block-wise encryption and decryption algorithms are available online.
The document provides an introduction to image encryption using AES key expansion. It discusses how traditional encryption techniques are not well-suited for encrypting large multimedia files like images due to their size and characteristics. The objective of the study is to develop an image encryption system that is computationally secure, fast enough for real-time use, and widely acceptable. It reviews related works in image encryption and discusses limitations of only using a 128-bit AES key. The document is organized into chapters covering cryptography fundamentals, image cryptosystems, AES algorithm details, an example of AES key expansion, and experimental analysis.
This document discusses steganography and image steganography techniques. It defines steganography as hiding information within other information to avoid detection. Image steganography is described as hiding data in digital images using techniques like least significant bit encoding. The document outlines the LSB algorithm, which replaces the least significant bits of image pixel values with bits of the hidden message. Examples are given to illustrate how short messages can be concealed in an image using this method.
A Secure Data Communication System Using Cryptography and SteganographyIJCNCJournal
The information security has become one of the most significant problems in data communication. So it
becomes an inseparable part of data communication. In order to address this problem, cryptography and
steganography can be combined. This paper proposes a secure communication system. It employs
cryptographic algorithm together with steganography. The jointing of these techniques provides a robust
and strong communication system that able to withstand against attackers. In this paper, the filter bank
cipher is used to encrypt the secret text message, it provide high level of security, scalability and speed.
After that, a discrete wavelet transforms (DWT) based steganography is employed to hide the encrypted
message in the cover image by modifying the wavelet coefficients. The performance of the proposed system
is evaluated using peak signal to noise ratio (PSNR) and histogram analysis. The simulation results show
that, the proposed system provides high level of security.
A SECURE DATA COMMUNICATION SYSTEM USING CRYPTOGRAPHY AND STEGANOGRAPHY IJCNCJournal
The information security has become one of the most significant problems in data communication. So it
becomes an inseparable part of data communication. In order to address this problem, cryptography and
steganography can be combined. This paper proposes a secure communication system. It employs
cryptographic algorithm together with steganography. The jointing of these techniques provides a robust
and strong communication system that able to withstand against attackers. In this paper, the filter bank
cipher is used to encrypt the secret text message, it provide high level of security, scalability and speed.
After that, a discrete wavelet transforms (DWT) based steganography is employed to hide the encrypted
message in the cover image by modifying the wavelet coefficients. The performance of the proposed system
is evaluated using peak signal to noise ratio (PSNR) and histogram analysis. The simulation results show
that, the proposed system provides high level of security.
A New Approach of Cryptographic Technique Using Simple ECC & ECFIJAEMSJORNAL
Cryptography is the technique in which usually a file is converted into unreadable format by using public key and private key system called as public key cryptosystem. Then as per the user requirement that file is send to another user for secure data transmission. In this paper we purposed an image based cryptography that Elliptic Curve Function (ECF) techniques and pseudo random encoding technique on images to enhance the security of RFID communication. In the ECF approach, the basic idea is to replace the Elliptic Curve Function (ECF) of the cover image with the Bits of the messages to be hidden without destroying the property of the cover image significantly. The ECF based technique is the most challenging one as it is difficult to differentiate between the cover object and Crypto object if few ECF bits of the cover object are replaced. In Pseudo Random technique, a random key is used as seed for the Pseudo Random Number Generator in needed in the embedding process. Both the techniques used a Crypto key while embedding messages inside the cover image. By using the key, the chance of getting attacked by the attacker is reduced.
RSA Based Secured Image Steganography Using DWT ApproachIJERA Editor
The need for keeping safe secrecy of secret and sensitive data has been ever increasing with the new
developments in digital system. In this paper, we present an increased way for getting embedding encrypted
secret facts in gray scale images to give high level safety of facts for news over unsecured narrow channels
Cryptography and Steganography are two closely related techniques are used in proposed system. Cryptography
gets into making one of religion the secret note into a non-recognizable chipper. Steganography is then sent in
name for using Double-Stegging to fix this encrypted data into a cover thing by which something is done and
keeps secret its existence.
A Comparative Study And Literature Review Of Image Steganography TechniquesRick Vogel
This document reviews and compares various image steganography techniques that have been proposed by researchers. It begins with defining steganography as hiding communication to prevent detection by enemies. Image steganography techniques hide data in digital images by modifying pixel values. The document evaluates techniques based on invisibility, payload capacity, robustness, file format independence, and image quality using PSNR. Several literature examples are reviewed, including techniques using integer wavelet transform, bit plane complexity analysis, data compression prior to embedding, and transformations like DCT and Arnold transform for increased security. Overall the document provides an overview of image steganography concepts and a comparative analysis of different proposed techniques.
Information hiding in edge location of video using amalgamate fft and cubic s...IAEME Publication
This document summarizes a research paper that proposes a new video steganography technique. The technique encrypts a secret message using RSA before embedding it in pre-determined pixel locations of video frames. Edge detection is used to find control points for cubic spline interpolation, which dynamically determine the pixel locations. The secret bits are embedded in the least significant bits and real parts of the Fast Fourier Transform of pixel values. Experimental results show the technique maintains high video quality with minimal degradation, as measured by average PSNR and MSE values. The technique aims to increase security by hiding the locations and parameters used to extract the secret message.
This document summarizes a research paper that proposes a conditional entrench spatial domain steganography technique (CESS). CESS embeds secret information in the least significant bit and most significant bit of cover images based on predefined conditions to increase security and capacity. It decomposes cover images into 8x8 blocks. The first block embeds upper and lower bound values used for payload retrieval. Each subsequent 8x8 block embeds the payload in LSBs and MSBs of pixels based on the block's mean of median values and difference between consecutive pixels. The technique is evaluated based on capacity, security and PSNR compared to existing methods.
Steganography using visual cryptography: ReportAparna Nk
This document is a seminar report submitted by Aparna N K to the University of Kerala in partial fulfillment of the requirements for a Master of Computer Applications degree. The report discusses steganography using a genetic algorithm along with visual cryptography for wireless network applications. It provides background on steganography, cryptography, genetic algorithms, the LSB steganography algorithm, and describes a proposed system that uses LSB embedding combined with genetic algorithm pixel modification and visual cryptography to hide secret messages in images for secure transmission. The performance of the proposed system is analyzed based on metrics like mean squared error and peak signal-to-noise ratio.
Secure Image Hiding Algorithm using Cryptography and SteganographyIOSR Journals
This document proposes a secure image hiding algorithm using cryptography and steganography. It first encrypts an image using the Blowfish encryption algorithm. Then, it hides the encrypted image in a video file using least significant bit (LSB) steganography. Blowfish was chosen for encryption due to its strong security and fast processing compared to other algorithms. LSB steganography in BMP images provides high invisibility and payload capacity. The proposed method provides two layers of security by encrypting the image before hiding it, making it difficult for unauthorized users to detect or extract the hidden information.
DCT Based Secret Image Hiding In Video SequenceIJERA Editor
Internet which is ever more accessible to interference by not with authority people over the World. It is important to bring down a chance of Information being sensed while Transmitting is the major issue these days. To overcome these problems one of the solution is cryptography. There will be no solitude once it is decoded. So hiding data to make it confidential. Copyright is one of the ways for hiding data and it is security for digital media. Its significance and techniques used in executing hiding of data let us see in brief. The existing LSB modification technique as in this approach the bits are randomly distributes the bits of message in image so which will becomes complex for anonymous persons to extract original message information, it opens the gates for loosing important hidden information. Here hiding and extraction method is used for AVI (Audio Video Interleave). As Higher order coefficients maintains Secret message bits. The hidden information will be in the form of gray scale image pixel values. Grayscale value then converted into binary values .The resultant binary values will be assigned to the higher order coefficient values of DCT of AVI video frames. These experiments were successful. We can analyze the results using Mat lab simulation software.
This document discusses message transfer using steganography. Steganography is used to hide information like text, images or videos within other media files such as images, videos or music. The document discusses how steganography can be used to securely transfer messages between two parties by hiding the messages within digital files like images without the server being able to decrypt the messages. It discusses how the least significant bits of pixels can be modified to embed secret data without significantly affecting the cover image. Different encryption techniques for embedding the data are also discussed. The document concludes that steganography can help protect messages not only from intruders but also from server-side attacks by making it difficult for the server to detect and decrypt embedded messages.
High Security Cryptographic Technique Using Steganography and Chaotic Image E...IOSR Journals
This document summarizes a proposed cryptographic technique that combines steganography and chaotic image encryption to provide high security. Steganography is used to hide a message within a cover image by embedding it in the least significant bits of pixel values without affecting image quality. The resulting stego-image is then encrypted using triple-key chaotic image encryption based on the logistic map, making the encrypted data highly sensitive to changes in the initial encryption keys. The technique provides four layers of security to securely transmit hidden messages within digital images.
Secure Image Transmission for Cloud Storage System Using Hybrid SchemeIJERD Editor
- Data over the cloud is transferred or transmitted between servers and users. Privacy of that
data is very important as it belongs to personal information. If data get hacked by the hacker, can be
used to defame a person’s social data. Sometimes delay are held during data transmission. i.e. Mobile
communication, bandwidth is low. Hence compression algorithms are proposed for fast and efficient
transmission, encryption is used for security purposes and blurring is used by providing additional
layers of security. These algorithms are hybridized for having a robust and efficient security and
transmission over cloud storage system.
Security System for Data Using Steganography and Cryptography (SSDSC) csandit
1) The document describes a Security System for Data using Steganography and Cryptography (SSDSC) that encrypts documents using AES encryption, hides the encrypted data in an image using LEAST SIGNIFICANT BIT steganography, and transmits the image over the internet while keeping the document contents secure.
2) It detects objects in the cover image that are suitable for hiding data, hides the encrypted data in the least significant bits of pixels in the selected regions, and extracts and decrypts the data on the receiving end.
3) Testing showed the hidden and cover images were nearly identical with only small pixel differences, and over 97% similarity, demonstrating the effectiveness of the system in concealing
SECURITY SYSTEM FOR DATA USING STEGANOGRAPHY AND CRYPTOGRAPHY (SSDSC) cscpconf
1) The document describes a Security System for Data using Steganography and Cryptography (SSDSC) that encrypts documents using AES encryption, hides the encrypted data in an image using LEAST SIGNIFICANT BIT steganography, and transmits the image over the internet while keeping the document contents secure.
2) It detects non-important image regions using object detection and hides the encrypted data in the least significant bits of pixels in those regions.
3) The system was tested and results showed the hidden and original images were nearly identical with only small pixel differences, demonstrating the effectiveness of the hiding technique.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
IRJET- Machine Learning Application for Data SecurityIRJET Journal
1) The document proposes a machine learning approach for improving data security through steganography. It hides secret messages in images by modifying pixel values and uses machine learning models like SVM and DNN for smoothing distorted images and retrieving lost data.
2) The method first appends a secret text file onto an image, then performs image-to-image steganography to provide additional security. It decrypts the stego images and uses an SVM for classification and noise removal, along with a DNN network model.
3) Experimental results show that as the size of the hidden text file increases, more noise is introduced, but the machine learning models can effectively smooth the images and retrieve the lost message bits.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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Scalable face image retrieval using attribute enhanced sparse codewordsIEEEFINALYEARPROJECTS
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Scalable face image retrieval using attribute enhanced sparse codewordsIEEEFINALYEARPROJECTS
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Geo community-based broadcasting for data dissemination in mobile social netw...IEEEFINALYEARPROJECTS
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Utility privacy tradeoff in databases an information-theoretic approachIEEEFINALYEARPROJECTS
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Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
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Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
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Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
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We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
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This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
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Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
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Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
1. Extracting Spread-Spectrum Hidden Data from Digital Media
ABSTRACT
We consider the problem of extracting blindly data embedded over a wide band in a spectrum
(transform) domain of a digital medium (image, audio, video). We develop a novel multicarrier/
signature iterative generalized least-squares (M-IGLS) core procedure to seek unknown data hidden
in hosts via multicarrier spread-spectrum embedding. Neither the original host nor the embedding
carriers are assumed available. Experimental studies on images show that the developed algorithm
can achieve recovery probability of error close to what may be attained with known embedding
carriers and host autocorrelation matrix.
EXISTING SYSTEM
In the existing system reversible data hiding technique the image is compressed and
encrypted by using the encryption key and the data to hide is embedded in to the image by using
the same encryption key. The user who knows the secret encryption key used can access the image
and decrypt it after extracting or removing the data hidden in the image. After extracting the data
hidden in the image then only can be the original image is retrieved.
PROPOSED SYSTEM
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2. We propose the information hiding concept to reduce the risk of using cryptographic
algorithms alone. Data hiding techniques embed information into another medium making it
imperceptible to others, except for those that are meant to receive the hidden information and are
aware of it presence. It focuses on methods of hidden data in which cryptographic algorithms are
combined with the information hiding techniques to increase the security of transmitted data.
We focus our attention on the blind recovery of secret data hidden in medium hosts via
multi-carrier/signature direct-sequence spread-spectrum transform domain embedding.
MODULE DESCRIPTION:
Steganography:
Steganography includes the concealment of information within computer files. In
digital steganography, electronic communications may include steganographic coding
inside of a transport layer, such as a document file, image file, program or protocol
Digital steganography can hide confidential data (i.e. secret files) very securely by
embedding them into some media data called "vessel data." The vessel data is also referred to as
"carrier, cover, or dummy data". In Steganography images used for vessel data. The embedding
operation in practice is to replace the "complex areas" on the bit planes of the vessel image with the
confidential data. The most important aspect of Steganography is that the embedding capacity is
very large. For a 'normal' image, roughly 50% of the data might be replaceable with secret data
before image degradation becomes apparent.
Multi-Carrier Spread Spectrum Embedding:
The technique of spread spectrum may allow partly to fulfill the above requirements.
Advantages of spread spectrum techniques are widely known: Immunity against multi-path
distortion, no need for fiequency planning, high flexibility and variable data rate transmission. The
capability of minimising multiple access interference in direct-sequence code- division-multiple-
access system is given by the cross-correlation properties of spreading codes. In the case of multi-
path propagation the capability of distinguishing one component fiom thers in the composite
received signal is offered by the auto-correlation roperties of the spreading codes.
3. Image encryption and watermarking:
The host image is an 8-bit or higher grey level image which must ideally be the same size as
the plaintext image or else resized accordingly using the same proportions.
Pre-conditioning the cipher and the convolution processes are undertaken using a Discrete
Fourier Transform (DFT).
The output will include negative floating point numbers upon taking the real component of a
complex array. The array must be rectified by adding the largest negative value in the output array
to the same array before normalization.
For color host images, the binary cipher text can be inserted into one or all of the RGB
components.
The binary plaintext image should have homogeneous margins to minimize the effects of
ringing due to ‘edge effects’ when processing the data using Fourier transform.
Image decryption and extraction:
(i) The correlation operation should be undertaken using a DFT.
(ii) For color images, the data is decomposed into each RGB component and each 1-bit layer is
extracted and correlated with the appropriate cipher.
(iii) The output obtained in Step 3 has a low dynamic range and therefore requires to be quantized
into an 8-bit image based on floating point numbers within the range max (array)-min (array).
System Configuration:-
H/W System Configuration:-
Processor - Pentium –III
4. Speed - 1.1 Ghz
RAM - 256 MB(min)
Hard Disk - 20 GB
Floppy Drive - 1.44 MB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
S/W System Configuration:-
Operating System :Windows XP / 7
Front End : JAVA, RMI, SWING
CONCLUSION
We considered the problem of blindly extracting unknown messages hidden in image hosts
via multi-carrier/signature spread-spectrum embedding. Neither the original host nor the
embedding carriers are assumed available. We developed a low complexity multi-carrier iterative
generalized least-squares (M-IGLS) core algorithm. Experimental studies showed that M-IGLS can
achieve probability of error rather close to what may be attained with known embedding signatures
and known original host autocorrelation matrix and presents itself as an effective countermeasure
to conventional SS data embedding/ hiding5.