An Enhanced RGB Image Steganography Technique Using Dynamic Secret Key. Art of secret communication.
To place hidden information in a carrier.
Most efficient way to ensure the privacy.
Image steganography is the art of hiding information within digital images. The document discusses various techniques for image steganography including LSB (least significant bit) and DCT (discrete cosine transform). LSB is a simple spatial domain technique that replaces the least significant bits of image pixels with bits of a secret message. DCT operates in the frequency domain by transforming image blocks and hiding data in the mid-frequency DCT coefficients. The document compares the advantages and disadvantages of these techniques, and discusses their applications for hiding private information or digital watermarking. Metrics for analyzing steganography systems like bit error rate, mean square error, and peak signal to noise ratio are also introduced.
Biometric Hashing technique for AuthenticationAnIsh Kumar
This document summarizes a student project on bio-hashing authentication techniques. It includes an outline of topics to be covered such as types of cryptography, image encryption methods, cellular automata techniques like Langton's ant, and algorithms like Blowfish. The project is mentored by Dr. Debasis Giri and includes four students - Ankit Agarwal, Tuhin Kundu, Bachu Paul, and Anish Kumar. It aims to introduce bio-hashing authentication, discuss related work, and propose improvements such as generating a visually meaningful encrypted image.
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.
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.
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.
“Multimedia Steganography with Cipher Text and Compression ppt.Pradeep Vishwakarma
Multimedia Steganography with Cipher Text and Compression
This document discusses steganography techniques for hiding secret messages in various media formats. It describes how to embed messages in text, audio, images, and video files. For text, it explains using data compression like Huffman coding. Audio steganography slightly alters the binary sequence of sound files. Image steganography uses lossless compression to maintain image integrity while embedding data. Video steganography conceals any file within a carrier video. Statistical analysis can detect hidden messages by analyzing frequency distributions in covered files for abnormal patterns introduced during encoding.
Implementation of Image Steganography in Image by using FMM nested with LSB S...Praneeta Dehare
This document describes an implementation of image steganography that uses two techniques - Five Modulus Method (FMM) and Least Significant Bit (LSB) substitution - to hide a secret image within a cover image. The secret image is divided into two halves, with the upper half embedded using FMM and the lower half using LSB substitution. A private stego-key is also used during embedding to make detection of the secret image more difficult. The quality of the embedded and extracted images is evaluated using PSNR and MSE metrics, with the results showing good visual quality.
Image steganography is the art of hiding information within digital images. The document discusses various techniques for image steganography including LSB (least significant bit) and DCT (discrete cosine transform). LSB is a simple spatial domain technique that replaces the least significant bits of image pixels with bits of a secret message. DCT operates in the frequency domain by transforming image blocks and hiding data in the mid-frequency DCT coefficients. The document compares the advantages and disadvantages of these techniques, and discusses their applications for hiding private information or digital watermarking. Metrics for analyzing steganography systems like bit error rate, mean square error, and peak signal to noise ratio are also introduced.
Biometric Hashing technique for AuthenticationAnIsh Kumar
This document summarizes a student project on bio-hashing authentication techniques. It includes an outline of topics to be covered such as types of cryptography, image encryption methods, cellular automata techniques like Langton's ant, and algorithms like Blowfish. The project is mentored by Dr. Debasis Giri and includes four students - Ankit Agarwal, Tuhin Kundu, Bachu Paul, and Anish Kumar. It aims to introduce bio-hashing authentication, discuss related work, and propose improvements such as generating a visually meaningful encrypted image.
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.
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.
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.
“Multimedia Steganography with Cipher Text and Compression ppt.Pradeep Vishwakarma
Multimedia Steganography with Cipher Text and Compression
This document discusses steganography techniques for hiding secret messages in various media formats. It describes how to embed messages in text, audio, images, and video files. For text, it explains using data compression like Huffman coding. Audio steganography slightly alters the binary sequence of sound files. Image steganography uses lossless compression to maintain image integrity while embedding data. Video steganography conceals any file within a carrier video. Statistical analysis can detect hidden messages by analyzing frequency distributions in covered files for abnormal patterns introduced during encoding.
Implementation of Image Steganography in Image by using FMM nested with LSB S...Praneeta Dehare
This document describes an implementation of image steganography that uses two techniques - Five Modulus Method (FMM) and Least Significant Bit (LSB) substitution - to hide a secret image within a cover image. The secret image is divided into two halves, with the upper half embedded using FMM and the lower half using LSB substitution. A private stego-key is also used during embedding to make detection of the secret image more difficult. The quality of the embedded and extracted images is evaluated using PSNR and MSE metrics, with the results showing good visual quality.
Survey on Different Image Encryption Techniques with Tabular Formijsrd.com
Rapid growth of digital communication and multimedia application increases the need of security and it becomes an important issue of communication and storage of multimedia. Image Encryption is one of the techniques that are used to ensure high security. Various fields such as medical science military in which image encryption can be used. Recent cryptography provides necessary techniques for securing information and protective multimedia data. In last some years, encryption technology has been developed quickly and many image encryption methods have been used to protect confidential image data from illegal way in. Within this paper survey of different image encryption techniques have been discussed from which researchers can get an idea for efficient techniques to be used.
Designing Hybrid Cryptosystem for Secure Transmission of Image Data using Bio...ranjit banshpal
The document outlines a proposed hybrid cryptosystem for secure transmission of image data using biometric fingerprints. It discusses problems with existing password and cryptographic techniques, and proposes a system that uses fingerprint biometrics to generate an encryption key, JPEG compression, and a secret fragment visible mosaic image method for embedding encrypted image data. The methodology section describes the tools and algorithms used, including SHA-256, AES, and JPEG. The implementation details section provides flow diagrams of the encryption and decryption processes.
ON THE IMAGE QUALITY AND ENCODING TIMES OF LSB, MSB AND COMBINED LSB-MSBijcsit
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.
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.
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.
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.
This paper presents a general overview of the steganography. Steganography is the art of hiding the very presence of
communication by embedding secret messages into innocuous looking cover documents, such as digital images. Detection of
steganography, estimation of message length, and its extraction belong to the field of steganalysis. Steganalysis has recently received a
great deal of attention both from law enforcement and the media. In this paper review the what data types are supported, what methods
and information security professionals indetecting the use of steganography, after detection has occurred, can the embedded message
be reliably extracted, can the embedded data be separated from the carrier revealing the original file, and finally, what are some
methods to defeat the use of steganography even if it cannot be reliably detected.
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.
Dual Layer Security Of Data Using LSB Image Steganography And AES Encryption ...Bikash Chandra Prusty
In today’s scenario security of data is a very big challenge in any communication. The Digital Image Steganography is the science of hiding sensitive information in another transmission medium to achieve secure and secret communication.
The main motive of steganography is to hide the existence of communication.
This document summarizes steganography techniques for hiding data in digital images. It discusses how steganography hides secret messages in cover images such that a third party is unaware of the hidden data. The document focuses on the least significant bit (LSB) technique, where the LSB of image pixel values are replaced with bits of the secret message. It provides algorithms for embedding data into and extracting data from images using LSB matching. The document also discusses using gray scale images and separating images into RGB layers to increase embedding capacity while maintaining image quality.
This document describes a novel algorithm for image steganography using discrete wavelet transformation on a Beagle Board-XM. The algorithm uses discrete wavelet transformation and a modified AES technique to encrypt and hide a secret payload image in the LH, HL, and HH subbands of a cover image. The discrete wavelet transformation decomposes the cover image into frequency subbands. The secret image is encrypted using a modified AES algorithm before being embedded. This approach aims to provide better image quality and increased security compared to other steganography methods. The algorithm is implemented using the Beagle Board-XM and Open CV for reduced processing delays, costs, and resource requirements.
DATA HIDING BY IMAGE STEGANOGRAPHY APPLING DNA SEQUENCE ARITHMETIC & LSB INSE...Journal For Research
By Image Steganography we can hide the secret data in cover manner. Where present of secret information can’t realize or visible by malicious users. In this approach Steganography procedure divided into two steps. In first step, DNA sequence (combination of four nucleotides A, C, G & T) used to convert secret information into a key matrix by generating key. In second step, values of key matrix will steganography by Least Significant Bit (LSB) Insertion procedure. Advantage of this procedure is that secret information secured by secret key of DNA sequence and Steganography procedure.
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 summarizes and reviews research on combining image compression and encryption techniques. It begins by introducing the topic and noting that compression and encryption are often combined to improve efficiency and security of data transmission. It then categorizes the combinations into three types: encryption followed by compression, compression followed by encryption, and hybrid techniques that combine the two.
The document proceeds to summarize research on each combination type. For encryption followed by compression, it outlines research applying symmetric and asymmetric encryption with both lossless and lossy compression. For compression followed by encryption, it discusses how compression can improve security by removing redundancies before encryption. Finally, it notes emerging research on hybrid techniques that integrate compression and encryption in a single step.
This document presents a new image steganography technique called M16M (Mode 16 Method). It embeds secret messages into digital images in 3 steps: 1) selecting seed pixels, 2) choosing neighboring pixels, and 3) modifying pixel intensities according to the message bits. Modifying intensities slightly allows embedding large payloads without noticeable quality loss. Future directions may combine steganography with cryptography for stronger security or use it for digital watermarking applications. Steganography can enhance security for confidential documents and will likely be important for digital watermarking and copyright protection going forward.
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 Review of Comparison Techniques of Image SteganographyIOSR Journals
This document reviews and compares three common techniques for hiding information in digital images: Least Significant Bit (LSB) steganography, Discrete Cosine Transform (DCT) steganography, and Discrete Wavelet Transform (DWT) steganography. LSB is implemented in the spatial domain by replacing the least significant bits of cover image pixels with payload bits. DCT and DWT are implemented in the frequency domain by transforming the cover image and embedding payload bits in the transformed coefficients. The document evaluates and compares the performance of these three techniques based on metrics like mean squared error, peak signal-to-noise ratio, embedding capacity, and robustness.
PERFORMANCE ANALYSIS OF TEXT AND IMAGE STEGANOGRAPHY WITH RSA ALGORITHM IN CL...ijseajournal
Cloud computing provides a lot of shareable resources payable on demand to the users. The drawback with
cloud computing is the security challenges since the data in the cloud are managed by third party. Steganography and cryptography are some of the security measures applied in the cloud to secure user data. The objective of steganography is to hide the existence of communication from the unintended users whereas cryptography does provide security to user data to be transferred in the cloud. Since users pay for
the services utilize in the cloud, the need to evaluate the performance of the algorithms used in the cloud to
secure user data in order to know the resource consumed by such algorithms such as storage memory, network bandwidth, computing power, encryption and decryption time becomes imperative. In this work, we implemented and evaluated the performance of Text steganography and RSA algorithm and Image steganography and RSA as Digital signature considering four test cases. The simulation results show that, image steganography with RSA as digital signature performs better than text steganography and RSA algorithm. The performance differences between the two algorithms are 10.76, 9.93, 10.53 and 10.53 seconds for encryption time, 60.68, 40.94, 40.9, and 41.85 seconds for decryption time, 8.1, 10.92, 15.2 and 5.17 mb for memory used when hiding data, 5.3, 1.95 and 17.18 mb for memory used when extracting data, 0.93, 1.04, 1.36 and 3.76 mb for bandwidth used, 75.75, 36.2, 36.9 and 37.45 kwh for processing power used when hiding and extracting data respectively. Except in test case2 where Text steganography and RSA algorithm perform better than Image Steganography and RSA as Digital Signature in terms of memory used when extracting data with performance difference of -5.09 mb because of the bit size of the image data when extracted. This research work recommend the use of image steganography and RSA as digital signature to cloud service providers and users since it can secure major data types such as text, image, audio and video used in the cloud and consume less system resources.
Implementation of LSB-Based Image Steganography Method for effectiveness of D...ijsrd.com
Increased use of electronic communication has given birth to new ways of transmitting information securely. Steganography is a science of hiding information by embedding it in some other data called host message. Images are most known objects for steganography. The host message before steganography and stego message after steganography have the same characteristics. The given work is to be done by evaluating it on MATALAB. While evaluation one can calculate SNR, PSNR and BER for individual information Bit for conceal bit and analysis effect on results.
This document discusses an adaptive pixel value differencing (PVD) based secret data hiding technique. It begins with an introduction to steganography and some common steganography techniques. The proposed method aims to embed most data into edged areas of an image since there are larger pixel differences, increasing embedding capacity. It implements a PVD-based embedding and extraction algorithm. Experimental results on Lena and Baboon images show increased payload and acceptable stego image quality compared to LSB substitution. The proposed method effectively and efficiently embeds hidden information imperceptibly into cover images.
A Survey Paper On Different Steganography TechniqueJeff Brooks
This document summarizes a survey paper on different steganography techniques. It begins by defining steganography and its types such as linguistic, image, network, video, audio, and text steganography. It then focuses on least significant bit (LSB) steganography, explaining how it works by replacing the LSB of image pixel values with secret message bits. The paper compares the histograms of cover and stego images, showing they are almost identical. It discusses the advantages of steganography and concludes by analyzing steganography methods and suggesting areas for future work such as increasing embedding capacity while maintaining secrecy.
LSB Based Image Steganography for Information Security Systemijtsrd
Information hiding in a cover file is one of the most modernized and effective ways for transferring secret message from sender to receiver over the communication channel. There are many steganographic techniques for hiding secret message in image, text, audio, video and so on. Image Steganography is also one of the common methods used for hiding the information in the cover image. In this research work, the secret message is hidden in a cover image file using image steganography. LSB is very efficient algorithm used to embed the information in a cover file. The LSB based image steganography with various file sizes is analyzed and illustrated their results. Bitmap .bmp image is used as a cover image file to implement the proposed system. The detail Least Significant Bit LSB based image steganography is introduced. In this paper, the new embedding algorithm and extracting algorithm are presented. While embedding the secret message in a cover image file, the starting embedded pixel is chosen according to public shared key between sender and receiver. The original cover image and embedded image with secret message are analyzed with PSNR values and SNR values to achieve security. The resulting embedded image shows the acceptable PSNR and SNR values while comparing with the original cover image. The proposed system can help the information exchanging system over communication media. Aung Myint Aye "LSB Based Image Steganography for Information Security System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1 , December 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18995.pdf
http://www.ijtsrd.com/computer-science/computer-security/18995/lsb-based-image-steganography-for-information-security-system/aung-myint-aye
Survey on Different Image Encryption Techniques with Tabular Formijsrd.com
Rapid growth of digital communication and multimedia application increases the need of security and it becomes an important issue of communication and storage of multimedia. Image Encryption is one of the techniques that are used to ensure high security. Various fields such as medical science military in which image encryption can be used. Recent cryptography provides necessary techniques for securing information and protective multimedia data. In last some years, encryption technology has been developed quickly and many image encryption methods have been used to protect confidential image data from illegal way in. Within this paper survey of different image encryption techniques have been discussed from which researchers can get an idea for efficient techniques to be used.
Designing Hybrid Cryptosystem for Secure Transmission of Image Data using Bio...ranjit banshpal
The document outlines a proposed hybrid cryptosystem for secure transmission of image data using biometric fingerprints. It discusses problems with existing password and cryptographic techniques, and proposes a system that uses fingerprint biometrics to generate an encryption key, JPEG compression, and a secret fragment visible mosaic image method for embedding encrypted image data. The methodology section describes the tools and algorithms used, including SHA-256, AES, and JPEG. The implementation details section provides flow diagrams of the encryption and decryption processes.
ON THE IMAGE QUALITY AND ENCODING TIMES OF LSB, MSB AND COMBINED LSB-MSBijcsit
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.
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.
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.
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.
This paper presents a general overview of the steganography. Steganography is the art of hiding the very presence of
communication by embedding secret messages into innocuous looking cover documents, such as digital images. Detection of
steganography, estimation of message length, and its extraction belong to the field of steganalysis. Steganalysis has recently received a
great deal of attention both from law enforcement and the media. In this paper review the what data types are supported, what methods
and information security professionals indetecting the use of steganography, after detection has occurred, can the embedded message
be reliably extracted, can the embedded data be separated from the carrier revealing the original file, and finally, what are some
methods to defeat the use of steganography even if it cannot be reliably detected.
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.
Dual Layer Security Of Data Using LSB Image Steganography And AES Encryption ...Bikash Chandra Prusty
In today’s scenario security of data is a very big challenge in any communication. The Digital Image Steganography is the science of hiding sensitive information in another transmission medium to achieve secure and secret communication.
The main motive of steganography is to hide the existence of communication.
This document summarizes steganography techniques for hiding data in digital images. It discusses how steganography hides secret messages in cover images such that a third party is unaware of the hidden data. The document focuses on the least significant bit (LSB) technique, where the LSB of image pixel values are replaced with bits of the secret message. It provides algorithms for embedding data into and extracting data from images using LSB matching. The document also discusses using gray scale images and separating images into RGB layers to increase embedding capacity while maintaining image quality.
This document describes a novel algorithm for image steganography using discrete wavelet transformation on a Beagle Board-XM. The algorithm uses discrete wavelet transformation and a modified AES technique to encrypt and hide a secret payload image in the LH, HL, and HH subbands of a cover image. The discrete wavelet transformation decomposes the cover image into frequency subbands. The secret image is encrypted using a modified AES algorithm before being embedded. This approach aims to provide better image quality and increased security compared to other steganography methods. The algorithm is implemented using the Beagle Board-XM and Open CV for reduced processing delays, costs, and resource requirements.
DATA HIDING BY IMAGE STEGANOGRAPHY APPLING DNA SEQUENCE ARITHMETIC & LSB INSE...Journal For Research
By Image Steganography we can hide the secret data in cover manner. Where present of secret information can’t realize or visible by malicious users. In this approach Steganography procedure divided into two steps. In first step, DNA sequence (combination of four nucleotides A, C, G & T) used to convert secret information into a key matrix by generating key. In second step, values of key matrix will steganography by Least Significant Bit (LSB) Insertion procedure. Advantage of this procedure is that secret information secured by secret key of DNA sequence and Steganography procedure.
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 summarizes and reviews research on combining image compression and encryption techniques. It begins by introducing the topic and noting that compression and encryption are often combined to improve efficiency and security of data transmission. It then categorizes the combinations into three types: encryption followed by compression, compression followed by encryption, and hybrid techniques that combine the two.
The document proceeds to summarize research on each combination type. For encryption followed by compression, it outlines research applying symmetric and asymmetric encryption with both lossless and lossy compression. For compression followed by encryption, it discusses how compression can improve security by removing redundancies before encryption. Finally, it notes emerging research on hybrid techniques that integrate compression and encryption in a single step.
This document presents a new image steganography technique called M16M (Mode 16 Method). It embeds secret messages into digital images in 3 steps: 1) selecting seed pixels, 2) choosing neighboring pixels, and 3) modifying pixel intensities according to the message bits. Modifying intensities slightly allows embedding large payloads without noticeable quality loss. Future directions may combine steganography with cryptography for stronger security or use it for digital watermarking applications. Steganography can enhance security for confidential documents and will likely be important for digital watermarking and copyright protection going forward.
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 Review of Comparison Techniques of Image SteganographyIOSR Journals
This document reviews and compares three common techniques for hiding information in digital images: Least Significant Bit (LSB) steganography, Discrete Cosine Transform (DCT) steganography, and Discrete Wavelet Transform (DWT) steganography. LSB is implemented in the spatial domain by replacing the least significant bits of cover image pixels with payload bits. DCT and DWT are implemented in the frequency domain by transforming the cover image and embedding payload bits in the transformed coefficients. The document evaluates and compares the performance of these three techniques based on metrics like mean squared error, peak signal-to-noise ratio, embedding capacity, and robustness.
PERFORMANCE ANALYSIS OF TEXT AND IMAGE STEGANOGRAPHY WITH RSA ALGORITHM IN CL...ijseajournal
Cloud computing provides a lot of shareable resources payable on demand to the users. The drawback with
cloud computing is the security challenges since the data in the cloud are managed by third party. Steganography and cryptography are some of the security measures applied in the cloud to secure user data. The objective of steganography is to hide the existence of communication from the unintended users whereas cryptography does provide security to user data to be transferred in the cloud. Since users pay for
the services utilize in the cloud, the need to evaluate the performance of the algorithms used in the cloud to
secure user data in order to know the resource consumed by such algorithms such as storage memory, network bandwidth, computing power, encryption and decryption time becomes imperative. In this work, we implemented and evaluated the performance of Text steganography and RSA algorithm and Image steganography and RSA as Digital signature considering four test cases. The simulation results show that, image steganography with RSA as digital signature performs better than text steganography and RSA algorithm. The performance differences between the two algorithms are 10.76, 9.93, 10.53 and 10.53 seconds for encryption time, 60.68, 40.94, 40.9, and 41.85 seconds for decryption time, 8.1, 10.92, 15.2 and 5.17 mb for memory used when hiding data, 5.3, 1.95 and 17.18 mb for memory used when extracting data, 0.93, 1.04, 1.36 and 3.76 mb for bandwidth used, 75.75, 36.2, 36.9 and 37.45 kwh for processing power used when hiding and extracting data respectively. Except in test case2 where Text steganography and RSA algorithm perform better than Image Steganography and RSA as Digital Signature in terms of memory used when extracting data with performance difference of -5.09 mb because of the bit size of the image data when extracted. This research work recommend the use of image steganography and RSA as digital signature to cloud service providers and users since it can secure major data types such as text, image, audio and video used in the cloud and consume less system resources.
Implementation of LSB-Based Image Steganography Method for effectiveness of D...ijsrd.com
Increased use of electronic communication has given birth to new ways of transmitting information securely. Steganography is a science of hiding information by embedding it in some other data called host message. Images are most known objects for steganography. The host message before steganography and stego message after steganography have the same characteristics. The given work is to be done by evaluating it on MATALAB. While evaluation one can calculate SNR, PSNR and BER for individual information Bit for conceal bit and analysis effect on results.
This document discusses an adaptive pixel value differencing (PVD) based secret data hiding technique. It begins with an introduction to steganography and some common steganography techniques. The proposed method aims to embed most data into edged areas of an image since there are larger pixel differences, increasing embedding capacity. It implements a PVD-based embedding and extraction algorithm. Experimental results on Lena and Baboon images show increased payload and acceptable stego image quality compared to LSB substitution. The proposed method effectively and efficiently embeds hidden information imperceptibly into cover images.
A Survey Paper On Different Steganography TechniqueJeff Brooks
This document summarizes a survey paper on different steganography techniques. It begins by defining steganography and its types such as linguistic, image, network, video, audio, and text steganography. It then focuses on least significant bit (LSB) steganography, explaining how it works by replacing the LSB of image pixel values with secret message bits. The paper compares the histograms of cover and stego images, showing they are almost identical. It discusses the advantages of steganography and concludes by analyzing steganography methods and suggesting areas for future work such as increasing embedding capacity while maintaining secrecy.
LSB Based Image Steganography for Information Security Systemijtsrd
Information hiding in a cover file is one of the most modernized and effective ways for transferring secret message from sender to receiver over the communication channel. There are many steganographic techniques for hiding secret message in image, text, audio, video and so on. Image Steganography is also one of the common methods used for hiding the information in the cover image. In this research work, the secret message is hidden in a cover image file using image steganography. LSB is very efficient algorithm used to embed the information in a cover file. The LSB based image steganography with various file sizes is analyzed and illustrated their results. Bitmap .bmp image is used as a cover image file to implement the proposed system. The detail Least Significant Bit LSB based image steganography is introduced. In this paper, the new embedding algorithm and extracting algorithm are presented. While embedding the secret message in a cover image file, the starting embedded pixel is chosen according to public shared key between sender and receiver. The original cover image and embedded image with secret message are analyzed with PSNR values and SNR values to achieve security. The resulting embedded image shows the acceptable PSNR and SNR values while comparing with the original cover image. The proposed system can help the information exchanging system over communication media. Aung Myint Aye "LSB Based Image Steganography for Information Security System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1 , December 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18995.pdf
http://www.ijtsrd.com/computer-science/computer-security/18995/lsb-based-image-steganography-for-information-security-system/aung-myint-aye
Impact of Message Size on Least Significant Bit and Chaotic Logistic Mapping ...ijtsrd
Steganography is the technique of hiding information in other objects. Although many carrier objects can be used, digital images are the most popular because of their usage over the internet. For this purpose, many types of images steganographic techniques have been invented. Each of them has both pros and cons. It depends on the complexity, hiding capacity, security, and so on. In our research, we studied the two most popular techniques of image steganography, least significant bit LSB and chaotic logistic mapping to find the similarities, dissimilarities, and many other factors. In this paper, we presented a detailed comparison of the LSB and chaotic logistic mapping based image steganography for various carrier images and messages. Tokey Ahmmed | Ipshita Tasnim Raha | Faizah Safwat | Nakib Aman Turzo "Impact of Message Size on Least Significant Bit and Chaotic Logistic Mapping Steganographic Technique" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42494.pdf Paper URL: https://www.ijtsrd.comcomputer-science/computer-security/42494/impact-of-message-size-on-least-significant-bit-and-chaotic-logistic-mapping-steganographic-technique/tokey-ahmmed
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
Two level data security using steganography and 2 d cellular automataeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
A novel hash based least significant bit (2 3-3) image steganography in spati...ijsptm
The document presents a novel hash-based 2-3-3 least significant bit (LSB) image steganography technique for embedding secret images in the spatial domain of color cover images. The technique embeds 8 bits of secret image data at a time in the LSBs of color image pixels in a 2-3-3 pattern across the red, green, and blue channels. Experimental results show the proposed 2-3-3 technique improves mean squared error and peak signal-to-noise ratio values compared to the base 3-3-2 LSB insertion technique. The proposed technique provides better imperceptibility of the stego image and higher embedding capacity than previous hash-based LSB methods.
This document provides an overview of steganography. It discusses how steganography hides messages within carriers so that the message is concealed. The document then discusses the history of steganography dating back to ancient Greece. It also discusses modern uses of steganography during the Cold War and by terrorist groups. The document outlines the objectives of the study which are to provide security during message transmission. It then discusses steganography techniques like the LSB algorithm and provides snapshots of its implementation. Finally, it discusses the results of using LSB steganography and concludes with possibilities for further enhancement.
This document provides an overview of steganography. It discusses how steganography hides messages within carriers so that the message is concealed. The document then discusses the history of steganography dating back to ancient Greece. It also discusses modern uses of steganography during the Cold War and by terrorist groups. The document outlines the objectives of the study which are to provide security during message transmission. It then discusses steganography techniques like LSB substitution and how LSB works to embed messages in images. Snapshots of the designed steganography application are provided along with results discussing the efficiency of the LSB algorithm used. The document concludes by discussing future work to improve the technique.
analysis on concealing information within non secret dataVema Reddy
Steganography is the art of covered writing or hidden writing. The steganography can be done in six types of techniques, namely: substitution system technique, transform domain technique, spread spectrum technique, statistical method technique, distortion technique and cover generation technique. This ppt deals with substitution system technique and transforms domain technique. This ppt deals with four methods of steganography, namely: plain LSB steganography, inverted LSB steganography, pattern based steganography and twosided, threesided, foursided side matched methods
steganography. The performance and evaluation of these methods are shown in the ppt.
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.
Review On Encrypting and Decrypting Message Via Image SlicingIRJET Journal
This document reviews techniques for encrypting and decrypting messages via image slicing. It begins with an introduction on the importance of securing data transmitted over unsecured channels. It then summarizes several existing studies on steganography and cryptography techniques. The document proposes a hybrid approach using AES cryptography, LSB steganography, and image slicing/stitching for encrypting messages and ensuring their authentic transmission. It presents block diagrams of the sender and receiver sides and compares the proposed approach to existing systems. Limitations and opportunities for future work are also discussed.
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.
This document summarizes a technical seminar presentation on steganography. It introduces steganography as covert communication techniques that hide messages within other harmless media. It discusses the history of steganography dating back to ancient Greece. It then outlines the presentation sections on the problem statement, objectives, techniques like LSB algorithm, design phase with screenshots, results and discussion, and conclusion. The overall goal is securing data transmission by hiding messages in digital images.
IRJET-Securing High Capacity Data Hiding using Combined Data Hiding TechniquesIRJET Journal
This document presents a method for securing high capacity data hiding using combined data hiding techniques. The method encrypts a message using transposition cipher cryptography, applies a password, and then hides the encrypted message in an image using least significant bit steganography. Experimental results on hiding messages in various images found peak signal-to-noise ratios remained above 30 decibels, indicating hidden data did not noticeably degrade image quality. Statistical analysis of image parameters before and after hiding data also showed little difference, making the hidden message difficult to detect. The combination of encryption, password protection, and steganography provides three layers of security to better protect sizable messages.
Implementation of Steganographic Model using Inverted LSB InsertionDr. Amarjeet Singh
The most important thing in this insecure world is
the secrecy of everything. In today’s world, any important
data costs more than money. Steganography is the technique
in which one can hide data as a secrete in selected image. In
case of spatial domain, LSB approach is most popular in
steganography, where all the LSBs of pixels of image are
replaced by the bits of secret data. But the problem is that
the secrete can be easily guessed by the hacker and the data is
obtained by extracting it from direct LSBs. To make the
system more robust and to improve the signal to noise ratio,
the conventional LSB insertion method is replaced by
inverted LSB technic. The decision to invert or not the LSB
depends on combination of the 2nd and 3rd LSB. As not each
and every LSB is inverted, it makes the steganalysis very
difficult.
Optimized WES-System with Image Bit Embedding for Enhancing the Security of H...IRJET Journal
This document proposes an optimized security method for transmitting images over networks that combines watermarking, steganography, and embedding another image within the host image. The method works by first watermarking the host image in both its image and text form to obscure it. Then another image is embedded within the watermarked host image as a carrier, providing another layer of security. This combined output image is then transmitted to the receiver, who can extract both the original host image and watermark text using extraction techniques. The goal of this optimized approach is to provide stronger security and resistance to unauthorized access during transmission compared to prior individual techniques.
This document proposes a technique for hiding one image within another image using a combination of two steganography algorithms: the five modulus method (FMM) and least significant bit (LSB) substitution. The secret image is partitioned into two parts, with 75% hidden using FMM and 25% hidden using LSB substitution within the cover image. Additionally, a private stego-key is used with FMM to increase security. This nesting of algorithms along with a password is intended to make unauthorized extraction of the hidden image from the cover image more difficult. The document discusses related work in image steganography techniques and provides details of the proposed methodology. It is expected that this approach will achieve a good balance between security and
In the present scenario the use of images increased extremely in the cyber world so that we can
easily transfer data with the help of these images in a secured way. Image steganography becomes
important in this manner. Steganography and cryptography are the two techniques that are often confused
with each other. The input and output of steganography looks alike, but for cryptography the output will be
in an encrypted form which always draws attraction to the attacker. This paper combines both
steganography and cryptography so that attacker doesn’t know about the existence of message and the
message itself is encrypted to ensure more security. The textual data entered by the user is encrypted using
AES algorithm. After encryption, the encrypted data is stored in the colour image by using a hash based
algorithm. Most of the steganographic algorithms available today is suitable for a specific image format
and these algorithms suffers from poor quality of the embedded image. The proposed work does not corrupt
the images quality in any form. The striking feature is that this algorithm is suitable for almost all image
formats e.g.: jpeg/jpg, Bitmap, TIFF and GIFF.
Similar to A secured-rgb-image-steganography-using-secret-key (20)
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
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HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
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The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
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Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
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Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
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2. Understanding Edge (IoT)
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4. Deployment Using ArgoCD for Edge Devices
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5. Introduction to Apache Kafka and S3
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12. Jupyter Notebooks with Code Examples
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A secured-rgb-image-steganography-using-secret-key
1. Sk. Arman Ali (110241)
Palash Kumar Sarker(110243)
An Enhanced RGB Image
Steganography Tenique
Using Dynamic Secret Key
2. Outline
• Steganography
• Steganography and cryptography
• Objectives
• Literature Review
• Related Works
• Proposed System
• Experimental Result Analysis
• Conclusion
• References
3. Message
Steganography
• Art of secret communication.
• To place hidden information in a carrier.
• Most efficient way to ensure the privacy.
Steganography
Cover file(image,
audio, video)
Stego file(image,
audio, video)
5. Steganography and cryptography
• Same Purpose – To hide or protect important information.
• But different approach
Steganography – conceals information, making it unseen.
Cryptography – encrypts information, making it unreadable.
6. Objectives
• To pass a text through an image file in a
robust and advanced secured way.
• To embed secret information into only blue
channel of cover image.
• Better stego image quality.
• Dynamically embed to increase the security
using dynamic secret key.
7. Literature Review
DIGITAL APPROACHES
– Today, it often exists within digital
formats.
– It makes use of seemingly innocent cover files
such as text, audio, and image files.
– The embedded message may be anything that
can be encoded in binary
10. Literature Review(continued…)
REASONS FOR USING DIGITAL IMAGES
– It is the most widely used medium being used
today.
– Takes advantage of our limited visual perception
of colors.
– This field is expected to continually grow as
computer graphics power also grows.
– Many programs are available to apply
steganography.
11. IMAGE STEGANOGRAPHY
– Image steganography is a method of information
hiding into cover-image and generates a stego-image.
– This stego-image then sent the other party by known
medium, where the third party does not know that
this stego-image has hidden message.
– After receiving stego-image hidden message can
simply be extracted with or without stego-key
(depending on embedding algorithm) by the receiving
end
Literature Review(continued…)
12. Literature Review(continued…)
Types of image steganography
• Image domain
Also known as spatial domain techniques embed
messages in the intensity of the pixels directly.
• Transform domain
Also known as frequency domain, images are first
transformed and then the message is embedded in
the image.
14. Related work
Improved LSB Based Steganography Technique [1]
-Capacity is high.
-LSB(1-3-4 ) is used for data embedding .
Limitations
-Human eye is very sensitive in red and green color.
-For edge area, change all bits of blue channel and it
decreases image quality.
-Very much easy to attack the stego image.
-PSNR is low.
[1] Mamta Juneja and Parvinder S. Sandhu, “An Improved LSB Based Steganography Technique for RGB Color
Images”, International Journal of Computer and Communication Engineering, Vol.2, No.4, July 2013.
15. Related work(continued…)
New Approach for LSB Based Image Steganography using
Secret Key [2]
-Secret key encrypts the hidden information.
-Hidden information is stored into variable position of LSB of
image.
Limitations
-Green channel is used to store data.
-Low payload. capacity
-Easy to detect.
[2] S. M. Masud Karim, Md. Saifur Rahman and Md. Ismail Hossain, “A New Approach for LSB Based Image Steganography
using Secret Key”, Proceedings of 14th International Conference on Computer and Information Technology (ICCIT 2011) ,22-24
December, 2011, Dhaka, Bangladesh.
16. Related work(continued…)
Novel Approach to RGB Channel Based Image Steganography
Technique [3]
– High payload capacity.
– Pixel chosen dynamically.
Limitations
- Red, green and blue channel are used to store data.
- Low PSNR.
- Easy to detect the stego image.
[3]Gandharba Swain and Saroj Kumar Lenka, “A Novel Approach to RGB Channel Based Image Steganography
Technique”, International Arab Journal of e-Technology, Vol. 2, No. 4, June 2012.
17. Proposed System
Our proposed system is divided into two parts
Encoding Decoding
Message
Stegosystem
Encoder
Stego Image
Cover
Image
Stego Image
Stegosystem
Encoder
Message
Secret key
26. Conclusion
• Hiding data in best secured way.
• Bits are embedded into variable position of deeper
layer where variable position protects data against
intentional attacks.
• High robustness against intentional and unintentional
attack as well.
• The use of secret key gives a way to secure the
information from malicious user.
• Proposed system is implemented efficiently and most
robust, error free way.
• Dynamic secret key increases the security level.
27. References
[1] G. R. Manjula, A. Danti, “ Hash based least significant bit (2-3-3) image steganography in spatial domain”,
International Journal of Security, Privacy and Trust Management (IJSPTM) Vol. 4, No. 1, February 2015.
[2] S. M. Masud Karim, Md. Saifur Rahman and Md. Ismail Hossain, “A New Approach for LSB Based Image
Steganography using Secret Key”, Proceedings of 14th International Conference on Computer and Information
Technology (ICCIT 2011) 22-24 December, 2011, Dhaka, Bangladesh.
[3] G. Chugh, R.K. Yadav and R. Saini, “A New Image Steganographic Based on Mod Factor for RGB Images”
International Journal of Signal Processing, Image Processing and Pattern Recognition, Vol.7, No. 3,pp.27-44,
2014.
[4] A. K. Bairagi, “ASCII based Even-Odd Cryptography with Gray code and Image Steganography: A dimension in
Data Security”, ISSN 2218-5224 (Online, Vol. 01, Issue 02, Manuscript Code: 110112).
[5] A. K. Bairagi, S. Mondal, R. Debnath, ” A Robust RGB Channel Based Image Steganography Technique using
a Secret Key”, 16th Int'l Conf. Computer and Information Technology, 8-10 March 2014, Khulna, Bangladesh.
[6] Juneja, Sandhu, “an Improved LSB Based Steganography Technique for RGB Color Images”, International
Journal of Computer and Communication Engineering, Vol. 2, No. 4, July 2013.
[7] R. Bahirat, A. Kolhe, “Overview of Secure Data Transmission Using Steganography”, International Journal of
Emerging Technology and Advanced Engineering, Vol. 4, Issue 3, March 2014.