The document describes a technical seminar report on an adaptive LSB-OPAP based secret data hiding technique. It was submitted by Tejas.S, an undergraduate student of electronics and communication engineering at Amruta Institute of Engineering and Management Sciences, in partial fulfillment of the requirements for their bachelor's degree. The report discusses a new technique for embedding secret data into color or grayscale images using LSB substitution in an adaptive manner based on pixel intensity ranges. It aims to enhance embedding capacity and imperceptibility compared to traditional LSB techniques.
The document outlines the contents of a technical seminar on quantum computing. It discusses the research area of high performance computing and introduces the topic of quantum computing. It describes features like obeying quantum mechanics laws and using qubits. Applications mentioned include cryptography, teleportation, and artificial intelligence. A comparison table compares three research papers on different aspects related to addressing problems in quantum computing.
Images Steganography using Pixel Value Difference and Histogram AnalysisNortheastern University
A new data hiding method is proposed in this project , which can increase the steganographic security of a data hiding scheme .In this method a cover image is first mapped into a 1D pixels sequence by Hilbert filling curve and then it has been divided into non-overlapping embedding units .The division is made such that it gives two consecutive pixel values .As human eye has limited tolerance when it comes to texture and edge areas than in smooth areas , and as the difference between the pixel pairs in those areas are larger , therefore the method exploites pixel value difference (PVD) to solve out overflow underflow problem .
GSM Mobile Phone Based LCD Message Display SystemManish Kumar
This document is a project report submitted by students to fulfill the requirements for a bachelor's degree in electronics instrumentation and control engineering. It describes the development of a GSM mobile phone based LCD scrolling message display system. The system allows text messages to be sent via GSM and displayed on an LCD screen. The report includes chapters on introduction, literature survey, problem definition, system requirements, system modeling and design, implementation, testing, and conclusion. It provides details on the components used, software requirements, system design, and testing results.
This document is a self-study seminar report on steganography presented by Abhishek Singh. It includes an introduction to steganography, its importance, and a literature review on different steganographic techniques. The introduction defines steganography as hidden writing and discusses why it is important for secret communications. The literature review covers steganography methods in text, audio, images, and networks. It also discusses steganalysis, applications of steganography, and how it compares to cryptography.
The document provides details about a project report on security extensibility in steganography. It discusses existing steganography techniques like the Least Significant Bit (LSB) algorithm and their drawbacks. It proposes developing a new Security Extensibility Algorithm (SRM algorithm) to provide better security for steganography compared to the LSB algorithm. The SRM algorithm would be used for steganography, cryptography, password authentication, and digital watermarking. The report outlines the system analysis, design, and testing of the proposed SRM algorithms to enhance security when embedding secret messages within digital files.
While transferring a file from one point to another through Intranet and Internet we need more file secure concepts. Ordinary, file Encryption-Decryption Concepts, which are readily available in java examples are easily captured by middle way itself. So we need more security combination. This project helps to send a file from one place to another in a secured manner. Firstly the target file is encrypted and it is embedded into an audio or video or any media file. The resultant file will be protected by a password. This resultant media file is not changed in its original format and it can be run in the player, we can’t find any encrypted data inside it. This format will be sent through net. In the destination point it will be retrieved only by our software and giving the relevant password. So it is highly secured.
This document provides an overview of steganography. It defines steganography as hiding secret messages within other harmless messages to avoid detection by unauthorized parties. Various steganographic techniques are described, including hiding messages in digital files like images, audio, text and network protocols. Detection of steganography (steganalysis) and applications like digital watermarking and tamper proofing are also discussed. The document concludes by noting the importance of steganography and expectations for further advancement in the field.
This document outlines the requirements specification for a research project on video watermarking. The main aims of the project are to address copyright protection of digital video and develop a video watermarking scheme based on the Discrete Wavelet Transform using Matlab Simulink. The goals are to embed a watermark imperceptibly into video while making it robust against various attacks. The justification is that video faces increased attacks compared to other media. The work schedule outlines tasks from February to June 2015 including research, planning, analysis, design, coding and testing.
The document outlines the contents of a technical seminar on quantum computing. It discusses the research area of high performance computing and introduces the topic of quantum computing. It describes features like obeying quantum mechanics laws and using qubits. Applications mentioned include cryptography, teleportation, and artificial intelligence. A comparison table compares three research papers on different aspects related to addressing problems in quantum computing.
Images Steganography using Pixel Value Difference and Histogram AnalysisNortheastern University
A new data hiding method is proposed in this project , which can increase the steganographic security of a data hiding scheme .In this method a cover image is first mapped into a 1D pixels sequence by Hilbert filling curve and then it has been divided into non-overlapping embedding units .The division is made such that it gives two consecutive pixel values .As human eye has limited tolerance when it comes to texture and edge areas than in smooth areas , and as the difference between the pixel pairs in those areas are larger , therefore the method exploites pixel value difference (PVD) to solve out overflow underflow problem .
GSM Mobile Phone Based LCD Message Display SystemManish Kumar
This document is a project report submitted by students to fulfill the requirements for a bachelor's degree in electronics instrumentation and control engineering. It describes the development of a GSM mobile phone based LCD scrolling message display system. The system allows text messages to be sent via GSM and displayed on an LCD screen. The report includes chapters on introduction, literature survey, problem definition, system requirements, system modeling and design, implementation, testing, and conclusion. It provides details on the components used, software requirements, system design, and testing results.
This document is a self-study seminar report on steganography presented by Abhishek Singh. It includes an introduction to steganography, its importance, and a literature review on different steganographic techniques. The introduction defines steganography as hidden writing and discusses why it is important for secret communications. The literature review covers steganography methods in text, audio, images, and networks. It also discusses steganalysis, applications of steganography, and how it compares to cryptography.
The document provides details about a project report on security extensibility in steganography. It discusses existing steganography techniques like the Least Significant Bit (LSB) algorithm and their drawbacks. It proposes developing a new Security Extensibility Algorithm (SRM algorithm) to provide better security for steganography compared to the LSB algorithm. The SRM algorithm would be used for steganography, cryptography, password authentication, and digital watermarking. The report outlines the system analysis, design, and testing of the proposed SRM algorithms to enhance security when embedding secret messages within digital files.
While transferring a file from one point to another through Intranet and Internet we need more file secure concepts. Ordinary, file Encryption-Decryption Concepts, which are readily available in java examples are easily captured by middle way itself. So we need more security combination. This project helps to send a file from one place to another in a secured manner. Firstly the target file is encrypted and it is embedded into an audio or video or any media file. The resultant file will be protected by a password. This resultant media file is not changed in its original format and it can be run in the player, we can’t find any encrypted data inside it. This format will be sent through net. In the destination point it will be retrieved only by our software and giving the relevant password. So it is highly secured.
This document provides an overview of steganography. It defines steganography as hiding secret messages within other harmless messages to avoid detection by unauthorized parties. Various steganographic techniques are described, including hiding messages in digital files like images, audio, text and network protocols. Detection of steganography (steganalysis) and applications like digital watermarking and tamper proofing are also discussed. The document concludes by noting the importance of steganography and expectations for further advancement in the field.
This document outlines the requirements specification for a research project on video watermarking. The main aims of the project are to address copyright protection of digital video and develop a video watermarking scheme based on the Discrete Wavelet Transform using Matlab Simulink. The goals are to embed a watermark imperceptibly into video while making it robust against various attacks. The justification is that video faces increased attacks compared to other media. The work schedule outlines tasks from February to June 2015 including research, planning, analysis, design, coding and testing.
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.
Blue Eyes technology uses cameras and microphones to identify a user's actions and emotions in order to build machines that can understand human feelings and behaviors. It was developed by IBM to create computers with human-like perceptual and sensory abilities. The technology utilizes several components and techniques including emotion mouse, expression glasses, speech recognition, and eye tracking to analyze physiological data and determine a user's emotional state. It aims to develop more natural human-computer interaction and reduce human limitations. Potential applications of Blue Eyes technology include customer analysis in retail, vehicle safety systems, and medical operating systems.
Digital Watermarking describes methods and technologies that hide information, for example a number or text, in digital media, such as images, video. The embedding takes place by manipulating the content of the digital data, which means the information is not embedded in the frame around the data. The hiding process has to be such that the modifications of the media are imperceptible. For images this means that the modifications of the pixel values have to be invisible.
A digital watermark is a message which is embedded into digital content (video, images or text) that can be detected or extracted later. Moreover, in image the actual bits representing the watermark must be scattered throughout the file in such a way that they cannot be identified and manipulated. Watermarking is the insertion of imperceptible and inseparable information into the host data for data security & integrity. They are characterizing patterns, of varying visibility, added to the presentation media as a guarantee of authenticity, quality, ownership, and source. However, in digital watermarking, the message is supposed not to visible (or at least not interfering with the user experience of the content), but (only) electronic devices can retrieve the embedded message to identify the code. Another form of digital watermarking is known as steganography, in which a message is hidden in the content without typical citizens or the public authorities noticing its presence. Only a limited number of recipients can retrieve and decode the hidden message. Unlike a traditional watermark on paper, which is generally visible to the eye, digital watermarks can be made invisible or inaudible. They can, however, be read by a computer with the proper decoding software.
Digital watermarks are embedded signals or patterns inserted into digital media like text, images, or video that carry copyright information. There are various techniques for watermarking different types of media. Watermarking leaves the original file intact while encryption transforms the file contents. Popular watermarking applications include ownership assertion, fingerprinting to trace copies, authentication and integrity verification, content labeling, usage control, and content protection with visible watermarks. Watermarks should be detectable, unambiguous, and robust against attacks. Text watermarking alters spacing, images can modify pixel values in spatial or frequency domains, and checksum techniques embed a checksum in pixel bits. However, early watermarking schemes provided only limited protection against removal or forgery.
This document provides an overview of magnetic levitation and its applications. It discusses various methods for achieving stable magnetic levitation, including mechanical constraints, diamagnetic levitation using superconductors, and servo stabilization. Applications covered include magnetic bearings, which reduce friction in machines by levitating rotating components, and maglev trains, which use magnetic levitation for contactless high-speed transportation. The document also outlines challenges such as instability based on Earnshaw's theorem and the need for continuous power input in active magnetic bearing systems.
The document discusses the Sky-X technology, which replaces TCP with the Xpress Transport Protocol (XTP) for satellite communication. The Sky-X gateway intercepts TCP connections and converts data to XTP for transmission over the satellite link, then back to TCP. This improves performance over satellite links by optimizing for high loss environments compared to TCP. The Sky-X system allows networks to take full advantage of satellite bandwidth and provides fast, reliable data transfer and multicast file transfers without requiring client/server modifications.
The document is a student project report on image steganography. It discusses using the least significant bit (LSB) method to hide information in digital images. The summary is:
1. It introduces steganography and LSB methods for hiding data in digital images by replacing the least significant bits of pixels.
2. Code is presented to embed a hidden message in an image by modifying pixels' LSBs and decoding the message from the stego image.
3. The report evaluates LSB steganography's advantages for covert communication but notes room for improving embedding capacity while maintaining secrecy.
Steganography and Its Applications in SecurityIJMER
ABSTRACT: Steganography is the dark cousin of cryptography, the use of codes. While cryptography provides privacy,
steganography is intended to provide secrecy. Steganography is a method of covertly communicating. Steganography is a
process that involves hiding a message in an appropriate carrier for example an image or an audio file. The carrier can then
be sent to a receiver without anyone else knowing that it contains a hidden message. This is a process, which can be used for
example by civil rights organizations in repressive states to communicate their message to the outside world without their
own government being aware of it. In this article we have tried to elucidate the different approaches towards implementation
of Steganography using ‘multimedia’ file (text, static image, audio and video). Steganalysis is a newly emerging branch of
data processing that seeks the identification of steganographic covers, and if possible message extraction. It is similar to
cryptanalysis in cryptography. The technique is ancient emerging monster that have gained immutable notice as it have
newly penetrated the world of digital communication security. Objective is not only to prevent the message being read but
also to hide its existence.
Keywords: Carrier, Privacy, Secrecy, Steganalysis, Steganography
LICENSE NUMBER PLATE RECOGNITION SYSTEM USING ANDROID APPAditya Mishra
The document outlines the development of a number plate recognition system using optical character recognition, including analyzing existing approaches, designing the system architecture, specifying functional and non-functional requirements, and testing the system. It also provides integrated summaries of several research papers on topics like automatic number plate recognition, optical character recognition techniques, and license plate recognition using OCR and template matching.
IRJET- Charging Station for Electric Vehicles using RF ModuleIRJET Journal
1. The document describes a prototype for an electric vehicle charging station that uses RFID technology for user identification and authorization.
2. The charging station system uses an RF transmitter and receiver module along with a microcontroller to control relays and charge the vehicle battery for different lengths of time depending on which button the user presses.
3. The system is designed to be low-cost and provides contactless charging authorization through RFID to simplify the charging process for electric vehicle users.
This document discusses steganography techniques for hiding secret information in digital images. It begins with an introduction to steganography and its differences from cryptography. It then discusses various steganography techniques including least significant bit insertion, masking and filtering, and transform domain techniques. It also discusses using bitmap images for steganography and the popularity of formats like JPEG. The goal of the document is to provide an overview of digital image steganography techniques.
VIRTUAL PAINT APPLICATION USING HAND GESTURESIRJET Journal
This document presents a virtual paint application that uses hand gesture recognition for real-time drawing or sketching. The application uses MediaPipe and OpenCV to track hand movements and joints in real-time. It identifies different gestures like selecting tools, writing on the canvas, and clearing the canvas. This allows for an intuitive human-computer interaction method without any physical devices. The application provides a dust-free classroom solution and makes online lessons more engaging. It analyzes video frames from a webcam to detect hand landmarks and identify gestures based on finger positions. This allows users to draw on screen by simply moving their hands.
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 provides an overview of image and audio steganography. It discusses the basics of steganography including its definition as concealed writing and a brief history of its use from ancient times to modern digital applications. The document focuses on different steganography techniques for images and audio, including least significant bit (LSB) encoding and decoding processes. It also includes system design diagrams and an implementation section describing a steganography program.
The document discusses steganography, which is the practice of hiding secret messages within other harmless messages or files. It provides an introduction and history of steganography, outlines the differences between steganography and cryptography, describes how to perform steganography using different media like images and audio, discusses digital watermarking techniques, and notes advantages and disadvantages of steganography.
This document is a project report for a BTech student named Rohit Jaiswal on image and audio steganography. It discusses hiding text messages in digital images and audio files. The report includes an introduction to steganography and cryptography, an analysis of digital images and audio, the design of the steganography system including algorithms, and implementations in C# and Flash. It also covers inputs, outputs, and conclusions with references and source code in the appendix. The supervisor of the project is Mr. Rajeev Srivastava of the Computer Science department at Banaras Hindu University.
The document discusses the history and types of electric and autonomous vehicles. It describes Thomas Edison's early electric car and the benefits of electric vehicles over gas-powered vehicles. The types of electric vehicles discussed are plug-in electric, hybrid electric, and plug-in hybrid vehicles. Google's self-driving car program and the development of autonomous vehicle technology over time is also summarized.
This document describes a mini project on steganography submitted by four students to fulfill the requirements of a computer science degree. It includes a cover page, certificates from advisors and department heads, acknowledgements, a declaration page, and a table of contents. The project involves developing an application for hiding secret messages in digital images using the least significant bit steganography technique. It covers encoding a message into an image, decrypting the message from the stego-image, and a user manual for the application. The objective is to explore data hiding and extraction techniques for secure communication.
This document discusses different types of steganalysis algorithms used to detect hidden messages embedded in digital files such as images, audio, and video. It describes specific steganalysis algorithms designed for certain embedding techniques as well as generic algorithms that can be applied broadly. Specific image steganalysis algorithms are discussed for formats like GIF, BMP, and JPEG. Audio steganalysis targets techniques like low-bit encoding, phase coding, spread spectrum coding, and echo hiding. Video steganalysis uses a framework with watermark attack and pattern recognition stages.
This document discusses steganography, which is hiding messages within seemingly harmless carriers or covers so that no one apart from the intended recipient knows a message has been sent. It provides examples of steganography in text, images, and audio, as well as methods used for each. These include techniques like least significant bit insertion and temporal sampling rates. The document also covers steganalysis, which aims to detect hidden communications by analyzing changes in the statistical properties of covers.
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.
Blue Eyes technology uses cameras and microphones to identify a user's actions and emotions in order to build machines that can understand human feelings and behaviors. It was developed by IBM to create computers with human-like perceptual and sensory abilities. The technology utilizes several components and techniques including emotion mouse, expression glasses, speech recognition, and eye tracking to analyze physiological data and determine a user's emotional state. It aims to develop more natural human-computer interaction and reduce human limitations. Potential applications of Blue Eyes technology include customer analysis in retail, vehicle safety systems, and medical operating systems.
Digital Watermarking describes methods and technologies that hide information, for example a number or text, in digital media, such as images, video. The embedding takes place by manipulating the content of the digital data, which means the information is not embedded in the frame around the data. The hiding process has to be such that the modifications of the media are imperceptible. For images this means that the modifications of the pixel values have to be invisible.
A digital watermark is a message which is embedded into digital content (video, images or text) that can be detected or extracted later. Moreover, in image the actual bits representing the watermark must be scattered throughout the file in such a way that they cannot be identified and manipulated. Watermarking is the insertion of imperceptible and inseparable information into the host data for data security & integrity. They are characterizing patterns, of varying visibility, added to the presentation media as a guarantee of authenticity, quality, ownership, and source. However, in digital watermarking, the message is supposed not to visible (or at least not interfering with the user experience of the content), but (only) electronic devices can retrieve the embedded message to identify the code. Another form of digital watermarking is known as steganography, in which a message is hidden in the content without typical citizens or the public authorities noticing its presence. Only a limited number of recipients can retrieve and decode the hidden message. Unlike a traditional watermark on paper, which is generally visible to the eye, digital watermarks can be made invisible or inaudible. They can, however, be read by a computer with the proper decoding software.
Digital watermarks are embedded signals or patterns inserted into digital media like text, images, or video that carry copyright information. There are various techniques for watermarking different types of media. Watermarking leaves the original file intact while encryption transforms the file contents. Popular watermarking applications include ownership assertion, fingerprinting to trace copies, authentication and integrity verification, content labeling, usage control, and content protection with visible watermarks. Watermarks should be detectable, unambiguous, and robust against attacks. Text watermarking alters spacing, images can modify pixel values in spatial or frequency domains, and checksum techniques embed a checksum in pixel bits. However, early watermarking schemes provided only limited protection against removal or forgery.
This document provides an overview of magnetic levitation and its applications. It discusses various methods for achieving stable magnetic levitation, including mechanical constraints, diamagnetic levitation using superconductors, and servo stabilization. Applications covered include magnetic bearings, which reduce friction in machines by levitating rotating components, and maglev trains, which use magnetic levitation for contactless high-speed transportation. The document also outlines challenges such as instability based on Earnshaw's theorem and the need for continuous power input in active magnetic bearing systems.
The document discusses the Sky-X technology, which replaces TCP with the Xpress Transport Protocol (XTP) for satellite communication. The Sky-X gateway intercepts TCP connections and converts data to XTP for transmission over the satellite link, then back to TCP. This improves performance over satellite links by optimizing for high loss environments compared to TCP. The Sky-X system allows networks to take full advantage of satellite bandwidth and provides fast, reliable data transfer and multicast file transfers without requiring client/server modifications.
The document is a student project report on image steganography. It discusses using the least significant bit (LSB) method to hide information in digital images. The summary is:
1. It introduces steganography and LSB methods for hiding data in digital images by replacing the least significant bits of pixels.
2. Code is presented to embed a hidden message in an image by modifying pixels' LSBs and decoding the message from the stego image.
3. The report evaluates LSB steganography's advantages for covert communication but notes room for improving embedding capacity while maintaining secrecy.
Steganography and Its Applications in SecurityIJMER
ABSTRACT: Steganography is the dark cousin of cryptography, the use of codes. While cryptography provides privacy,
steganography is intended to provide secrecy. Steganography is a method of covertly communicating. Steganography is a
process that involves hiding a message in an appropriate carrier for example an image or an audio file. The carrier can then
be sent to a receiver without anyone else knowing that it contains a hidden message. This is a process, which can be used for
example by civil rights organizations in repressive states to communicate their message to the outside world without their
own government being aware of it. In this article we have tried to elucidate the different approaches towards implementation
of Steganography using ‘multimedia’ file (text, static image, audio and video). Steganalysis is a newly emerging branch of
data processing that seeks the identification of steganographic covers, and if possible message extraction. It is similar to
cryptanalysis in cryptography. The technique is ancient emerging monster that have gained immutable notice as it have
newly penetrated the world of digital communication security. Objective is not only to prevent the message being read but
also to hide its existence.
Keywords: Carrier, Privacy, Secrecy, Steganalysis, Steganography
LICENSE NUMBER PLATE RECOGNITION SYSTEM USING ANDROID APPAditya Mishra
The document outlines the development of a number plate recognition system using optical character recognition, including analyzing existing approaches, designing the system architecture, specifying functional and non-functional requirements, and testing the system. It also provides integrated summaries of several research papers on topics like automatic number plate recognition, optical character recognition techniques, and license plate recognition using OCR and template matching.
IRJET- Charging Station for Electric Vehicles using RF ModuleIRJET Journal
1. The document describes a prototype for an electric vehicle charging station that uses RFID technology for user identification and authorization.
2. The charging station system uses an RF transmitter and receiver module along with a microcontroller to control relays and charge the vehicle battery for different lengths of time depending on which button the user presses.
3. The system is designed to be low-cost and provides contactless charging authorization through RFID to simplify the charging process for electric vehicle users.
This document discusses steganography techniques for hiding secret information in digital images. It begins with an introduction to steganography and its differences from cryptography. It then discusses various steganography techniques including least significant bit insertion, masking and filtering, and transform domain techniques. It also discusses using bitmap images for steganography and the popularity of formats like JPEG. The goal of the document is to provide an overview of digital image steganography techniques.
VIRTUAL PAINT APPLICATION USING HAND GESTURESIRJET Journal
This document presents a virtual paint application that uses hand gesture recognition for real-time drawing or sketching. The application uses MediaPipe and OpenCV to track hand movements and joints in real-time. It identifies different gestures like selecting tools, writing on the canvas, and clearing the canvas. This allows for an intuitive human-computer interaction method without any physical devices. The application provides a dust-free classroom solution and makes online lessons more engaging. It analyzes video frames from a webcam to detect hand landmarks and identify gestures based on finger positions. This allows users to draw on screen by simply moving their hands.
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 provides an overview of image and audio steganography. It discusses the basics of steganography including its definition as concealed writing and a brief history of its use from ancient times to modern digital applications. The document focuses on different steganography techniques for images and audio, including least significant bit (LSB) encoding and decoding processes. It also includes system design diagrams and an implementation section describing a steganography program.
The document discusses steganography, which is the practice of hiding secret messages within other harmless messages or files. It provides an introduction and history of steganography, outlines the differences between steganography and cryptography, describes how to perform steganography using different media like images and audio, discusses digital watermarking techniques, and notes advantages and disadvantages of steganography.
This document is a project report for a BTech student named Rohit Jaiswal on image and audio steganography. It discusses hiding text messages in digital images and audio files. The report includes an introduction to steganography and cryptography, an analysis of digital images and audio, the design of the steganography system including algorithms, and implementations in C# and Flash. It also covers inputs, outputs, and conclusions with references and source code in the appendix. The supervisor of the project is Mr. Rajeev Srivastava of the Computer Science department at Banaras Hindu University.
The document discusses the history and types of electric and autonomous vehicles. It describes Thomas Edison's early electric car and the benefits of electric vehicles over gas-powered vehicles. The types of electric vehicles discussed are plug-in electric, hybrid electric, and plug-in hybrid vehicles. Google's self-driving car program and the development of autonomous vehicle technology over time is also summarized.
This document describes a mini project on steganography submitted by four students to fulfill the requirements of a computer science degree. It includes a cover page, certificates from advisors and department heads, acknowledgements, a declaration page, and a table of contents. The project involves developing an application for hiding secret messages in digital images using the least significant bit steganography technique. It covers encoding a message into an image, decrypting the message from the stego-image, and a user manual for the application. The objective is to explore data hiding and extraction techniques for secure communication.
This document discusses different types of steganalysis algorithms used to detect hidden messages embedded in digital files such as images, audio, and video. It describes specific steganalysis algorithms designed for certain embedding techniques as well as generic algorithms that can be applied broadly. Specific image steganalysis algorithms are discussed for formats like GIF, BMP, and JPEG. Audio steganalysis targets techniques like low-bit encoding, phase coding, spread spectrum coding, and echo hiding. Video steganalysis uses a framework with watermark attack and pattern recognition stages.
This document discusses steganography, which is hiding messages within seemingly harmless carriers or covers so that no one apart from the intended recipient knows a message has been sent. It provides examples of steganography in text, images, and audio, as well as methods used for each. These include techniques like least significant bit insertion and temporal sampling rates. The document also covers steganalysis, which aims to detect hidden communications by analyzing changes in the statistical properties of covers.
The document provides an overview of steganography and steganalysis techniques. It discusses image file formats like BMP, JPEG and GIF and how they can be used to hide data. Common data hiding methods include least significant bit substitution and palette manipulation. Steganalysis techniques to detect hidden data include least significant bit analysis, chi-square tests and histogram analysis. Encrypting data before hiding can help prevent detection by statistical analysis.
This document discusses steganography and steganalysis. It begins with an introduction and overview of steganography techniques, including encryption, decryption, least significant bit insertion, and discrete cosine transformation. It then covers steganalysis approaches like statistical, structural, and visual analysis. The document outlines experiments conducted with least significant bit insertion to hide images in audio and image files. It analyzes the output for changes to statistical characteristics to detect hidden information. In conclusion, the document examines steganography and steganalysis as techniques for covertly hiding and detecting hidden data in digital files.
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.
Steganalysis of LSB Embedded Images Using Gray Level Co-Occurrence MatrixCSCJournals
This paper proposes a steganalysis technique for both grayscale and color images. It uses the feature vectors derived from gray level co-occurrence matrix (GLCM) in spatial domain, which is sensitive to data embedding process. This GLCM matrix is derived from an image. Several combinations of diagonal elements of GLCM are considered as features. There is difference between the features of stego and non-stego images and this characteristic is used for steganalysis. Distance measures like Absolute distance, Euclidean distance and Normalized Euclidean distance are used for classification. Experimental results demonstrate that the proposed scheme outperforms the existing steganalysis techniques in attacking LSB steganographic schemes applied to spatial domain.
This document provides an overview of steganography, including:
1) Steganography is the art of hiding information in plain sight so that the very existence of a hidden message is concealed. It works by embedding messages within images, audio, or other files.
2) Modern uses include digital watermarking to identify ownership, hiding sensitive files, and illegitimate uses like corporate espionage, terrorism, and child pornography.
3) Techniques include least significant bit insertion to replace bits in files, injection to directly embed messages, and generating new files from scratch. Detection methods like steganalysis aim to discover hidden information.
Steganography is the art and science of hiding information by embedding messages within other harmless media so as not to arouse suspicion. It differs from cryptography in that the goal is to conceal the very existence of the message, not just its content. Common techniques include hiding data in the least significant bits of images, altering text formatting, and embedding signals in audio files like echoes. Detection methods involve looking for anomalies introduced by hidden data or disabling embedded data through compression or filtering. Steganography has applications in secure communication, copyright protection, and covert messaging.
The document provides an overview of steganography, including its definition, history, techniques, applications, and future scope. It discusses different types of steganography such as text, image, and audio steganography. For image steganography, it describes techniques such as LSB insertion and compares image and transform domain methods. It also provides examples of steganography tools and their usage for confidential communication and data protection.
This document provides an overview of cryptography. It defines cryptography as the science of securing messages from attacks. It discusses basic cryptography terms like plain text, cipher text, encryption, decryption, and keys. It describes symmetric key cryptography, where the same key is used for encryption and decryption, and asymmetric key cryptography, which uses different public and private keys. It also covers traditional cipher techniques like substitution and transposition ciphers. The document concludes by listing some applications of cryptography like e-commerce, secure data, and access control.
This document summarizes a research paper that proposes a novel two-layer security mechanism combining cryptography and steganography techniques. The paper begins with an introduction discussing security issues with traditional cryptography and steganography methods. It then reviews related work in the fields. The proposed approach encrypts a secret message using AES encryption, splits the cipher file into frames, and embeds the cipher text in video frames using DCT-based steganography. Experimental results show the proposed approach achieves higher PSNR quality measurements than an existing HLSB technique, indicating better quality of stego frames. In addition, the proposed approach does not change file sizes compared to another existing approach.
This document summarizes a research paper on applying steganography techniques for data security. Specifically, it hides encrypted messages within digital images using the dynamic cell spreading technique (DCS) and the RC4 encryption algorithm. The document discusses DCS and RC4 in detail and evaluates the success of hiding encrypted messages in several test images without noticeable quality degradation. It concludes that DCS combined with RC4 encryption provides an effective method for hidden communication and data security.
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.
This document is a project report on image steganography submitted by Prabhat Kumar for their master's degree. It includes an abstract, introduction, synopsis, problem statement, objectives, and overview section describing steganography techniques. The report is investigating hiding secret information within digital images and evaluating different steganography methods.
Analysis of Different Steganography Algorithms and Security IssuesIRJAES Editor
This document analyzes and compares different steganography algorithms and their security issues. It discusses steganography techniques such as LSB (least significant bit) and DWT (discrete wavelet transform). LSB replaces least significant bits of cover media (such as images) with hidden data bits. DWT decomposes signals into different frequency bands with different resolutions. The document also addresses steganalysis, the process of detecting hidden messages within carrier files. It evaluates the capacity, detectability, and robustness of different steganography algorithms, noting strengths and limitations.
APPLICATION OF DATA HIDING IN AUDIO-VIDEO USING ANTIN FORENSICS TECHNIQUE FOR...ijiert bestjournal
The document discusses applying data hiding in audio-video files using anti-forensics techniques for authentication and data security. It proposes using steganography, which is hiding secret information in carrier files like audio and video, combined with anti-forensics techniques. The system would hide encrypted data in the least significant bits of frames in audio-video files. Parameters like PSNR and histograms would be analyzed at the transmitter and receiver ends to authenticate the data and ensure security. Common steganography algorithms like LSB and AES encryption would be used. The system aims to provide a more secure way of transferring data between client and server compared to traditional passwords or encryption alone.
This document is a seminar report on steganography presented by Tumma Ashwin to fulfill requirements for a B.Tech degree in Computer Engineering. It includes an introduction to steganography, principles of hiding data, types of steganography techniques, and methods for sending stego files across a network. The report was guided by Prof. S. U. Ghumbre and certifies that Tumma Ashwin completed the project work.
This document presents an adaptive steganography technique based on an enhanced cipher hiding method for secure data transfer. It combines cryptography and audio steganography. The secret message is first encrypted using a modified least significant bit algorithm and 2's complement operations. The encrypted data is then embedded into the least significant bits of an audio file. Keys are generated and sent with the stego audio to the receiver. The receiver uses the keys to extract the encrypted data from the audio and decrypt it back to the original message. The technique aims to provide better security for data transmission over unsecured networks by taking advantage of both cryptography and steganography.
Adaptive Steganography Based Enhanced Cipher Hiding Technique for Secure Data...iosrjce
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.
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 security using stegnography and quantum cryptographyAlexander Decker
The document proposes using a combination of steganography and quantum cryptography to securely transmit encrypted data. It begins by providing background on steganography, describing how it hides confidential information within cover files like images, and how it differs from encryption and digital watermarking. It then discusses related work improving steganography techniques. The proposed approach uses an advanced steganography algorithm (F5) to hide encrypted data within an image, making the secret information nearly impossible to detect. It also describes using quantum cryptography to securely generate and distribute the encryption key, providing virtually unbreakable security based on principles of quantum mechanics. The combination of steganography and quantum key distribution is argued to provide perfect security for transmitted data.
This document discusses various techniques for hiding secret information in digital video files for secure communication, known as video steganography. It begins by explaining steganography and comparing it to cryptography. It then discusses different video steganography methods, including least significant bit and spread spectrum approaches. It also covers combining steganography with encryption algorithms like AES. Previous research on video steganography is summarized, focusing on techniques that embed data in wavelet coefficients or motion vectors. The document concludes that further research could explore hiding moving images within video files using steganography and cryptography methods.
STEGANALYSIS ALGORITHM FOR PNG IMAGES BASED ON FUZZY LOGIC TECHNIQUEIJNSA Journal
The document presents an algorithm for detecting hidden messages in PNG images based on fuzzy logic techniques. It discusses steganography and steganalysis techniques such as LSB substitution and discusses their limitations in detecting hidden data in PNG files. The proposed system uses fuzzy logic for classifying images as clean or containing hidden messages. Experimental results show the fuzzy logic system achieved high performance in classifying PNG images.
This document summarizes a research paper that proposes using a hybrid genetic algorithm approach for data encryption. The system uses several modules: image steganography to hide data in images, image merging to combine encrypted images, musical encryption to encrypt data using musical patterns determined by a genetic algorithm, and a genetic algorithm module. The encryption process hides data in multiple files for stronger security. Decryption recovers the hidden data. The hybrid approach aims to provide stronger encryption that is more difficult to crack than existing algorithms.
Review paper on Data Security using Cryptography and Steganographyvivatechijri
One of the major problems faced by this digital world is Data Security. Data Security plays an important role in the field of information technology. As there are large advancements in internet technology, there has been huge text as well as multimedia data transfer over the internet. The communication channel available for data transfer from the transmitter to receiver is highly insecure. As the security of electronic data is a major issue and to achieve high security and confidentiality, the public and the private sectors use different kinds of techniques and methods to protect the data from unauthorized users. Cryptography and Steganography are the most popular and widely used technologies for security. Cryptography is the art of hiding information by encryption and steganography is a technique to hides data in the cover medium. Cryptography hides the readable and meaningful contents of the data. And the existence of the data is hidden by the Steganography technique.
Secure Message Transmission using Image Steganography on Desktop Basedijtsrd
The rapid increase in our technology has made easier for us to send and receive data over internet at most affordable way. There are many transmission medias like emails, facebook, twitter, etc” ¦ which led way for the intruders to modify and misuse the information what we share over the internet. So in order to overcome these kinds of issues many methods has been implemented such as Cryptography, Steganography and Digital watermarking to safeguard our data transmissions in a most prominent way. In this paper, hiding text inside a digital image using Stegano tool for secure data transmissions has been described. Sidharth Sai S | N. Priya "Secure Message Transmission using Image Steganography on Desktop Based" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd38067.pdf Paper URL : https://www.ijtsrd.com/computer-science/computer-security/38067/secure-message-transmission-using-image-steganography-on-desktop-based/sidharth-sai-s
IRJET- Concealing of Deets using Steganography TechniqueIRJET Journal
The document proposes a technique for concealing secret data in images using steganography by embedding audio data into the image pixels of different color planes and encrypting the data using an AES replacement algorithm. The proposed method aims to provide an efficient way to hide and extract data and audio independently without loss by embedding encrypted data into the least significant bits of pixels in a color image. The document evaluates the performance of the proposed multi-plane image and data hiding technique.
IRJET- Concealing of Deets using Steganography TechniqueIRJET Journal
The document proposes a technique for concealing secret data through multi-plane image data embedding and describes using AES replacement algorithm to conceal secret message bits into input image pixels. It discusses using steganography to hide cover data in unpredictable multimedia information for secret communication and extracting the hidden data and audio independently without loss by using the correct password. The proposed method aims to improve data hiding capacity while maintaining image quality.
11.secure data transmission by using steganographyAlexander Decker
This document summarizes a research paper that proposes a system for secure data transmission using steganography and cryptography. The system encrypts secret data using elliptic curve cryptography before embedding it in unused fields of the TCP/IP header to create a covert channel. This allows for covert transmission of encrypted data over a communication channel in a way that is not detectable by third parties. The paper reviews related work on using network protocols for steganography and discusses applying the proposed system to applications like secure file transfers and network auditing.
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1. VISVESVARAYA TECHNOLOGICAL
UNIVERSITY
JnanaSangama, Belgaum-590014
A Technical Seminar Report
On
“An Adaptive LSB-OPAPbased Secret Data Hiding”
Submitted in Partial fulfillment of the requirements for VIII semester
Bachelor of Engineering
in
Electronics & Communication Engineering
by
TEJAS.S
(1AR09EC043)
Under the Guidance of
Prof. PADMAJA VIJAYKUMAR
Dept. of ECE, AIeMS
DEPARTMENT OF ELECTRONICS AND COMMUNICATION
ENGINEERING
AMRUTA INSTITUTE OF ENGINEERING &
MANAGEMENT SCIENCES
Near bidadi industrial Area, Bengaluru-562109
2. B.V.V.Sangha’s
AMRUTA INSTITUTE OF ENGINEERING AND
MANAGEMENT SCIENCES
Near Bidadi Industrial Area, Bengaluru– 562109
DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING
CERTIFICATE
This is to Certify that the technical seminar entitled “An Adaptive LSB-OPAP based
Secret Data Hiding”has been carried out byTEJAS.S (1AR09EC043), a bonafide
student of Amruta institute of engineering & management sciences, in the partial
fulfillment of the requirements for the award of the degree in Bachelor of Engineering in
Electronics & Communication Engineering under Visvesvaraya Technological
University, Belgaum during the academic year 2012-2013. It is certified that all
corrections/suggestions indicated for Internal Assessment have been incorporated in the
report deposited in the department library.
Prof. PADMAJA VIJAYKUMAR Prof. C.R RAJAGOPAL
Dept of ECE, AIeMS HOD of ECE, AIeMS
Name of the Examiners: Signature and Date
1.
2.
3. ACKNOWLEDGEMENT
The satisfaction and euphoria that accompany the successful completion of any task
would be incomplete without the mention of the people who made it possible, whose constant
guidance and encouragement crowned my effort with success.
I am grateful to our institution, Amruta Institute of Engineering &
managementSciences (AIeMS) with its ideals and inspirations for having provided me with the
facilities, which made this, seminar a success.
I earnestly thank Dr. A. PRABHAKAR, Principal, AIeMS, for facilitating academic
excellence in the college and providing me with congenial environment to work in, that
helped me in completing this seminar.
I wish to extend my profound thanks to Prof. C.R.RAJAGOPAL, Head of the
Department, Electronics & Communication Engineering, AIeMS for giving me the
consent to carry out this seminar.
I would like to express my sincere thanks to our Internal Guide Prof. PADMAJA
VIJAYKUMAR, Department of Electronics & Communication Engineering, AIeMS for
her able guidance and valuable advice at every stage of my seminar, which helped me in the
successful completion of the seminar.
I wish to express my solicit thanks to my friend Mr. RAGHU.K for his help and
support to my seminar.
I am thankful to all the faculty members and non-teaching staff of the department for
their kind co-operation.
I also wish to thank my friends for their useful guidance on various topics. Last but
not the least, I would like to thank my parents and almighty for the support.
TEJAS.S
(1AR09EC043)
4. ABSTRACT
In the present digital world, Steganography and cryptography are excellent means by
which secret communication can be achieved significantly over the data network. The
classical methods of steganography such as LSB substitution involve hiding the data in a
multimedia carrier. The present research activities are focused on embedding the data and
simultaneously achieving good PSNR and efficient payload. An adaptive method for LSB
substitution with private stego-key based on gray-level ranges is proposed. This new
technique embeds binary secret data in 24-bits colour image or in 8-bits gray-scale image. In
this method the cover image pixels are grouped into 4 ranges based on their intensity levels.
Different ranks are allotted to each of the range so that the range having highest number of
pixel count gets the highest rank and the pixels under this range are embedded with
maximum of 4 bits of secret data. The pixel after embedding may or may not be within the
same range, hence this algorithm proposes an optimum pixel adjustment process (OPAP).
The method also verifies that whether the attacker has tried to modify the secret data
hidden inside the cover image. Besides, the embedded confidential information can be
extracted from stego-images without the assistance of original image. This method provides a
capacity of 3.5 bits/pixel and a PSNR of 52 dB on an average.
5. LIST OF FIGURES
page
Fig 1.1 Classification of Steganography 1
Fig 2.1 Method for k- bits insertion 6
Fig 3.1 LSB – OPAP 7
Fig 4.1 Message embedding with signature 10
Fig 4.2 Message extraction and integrity check 11
Fig 6.1 Experimental result using Range1 for Baboon cover image 14
Fig 6.2 Experimental result using Range2 for Lena cover image 15
6. TABLE OF CONTENTS
Page
1. Introduction to Steganography 1
2. An Adaptive LSB-OPAP employed pixel domain stegotechnique
(ALOS) 4
2.1 Proposed Methodology
2.2 Private stego-key generation
2.3 Method to decide Bits insertion in each range
2.4 LSB substitution
3. Optimum Pixel Adjustment Process (OPAP) 7
4. Implementation of ALOS 9
4.1 Algorithms: Embedding
4.2 Algorithms: Extracting
5.Advantages& Applications of proposed system 12
5.1 Advantages
5.2 Limitations
5.3 Applications
6. Experimental results and discussions 13
References
7. CHAPTER 1
INTRODUCTION TO STEGANOGRAPHY
Steganography is derived from the Greek for covered writing and essentially means
“to hide in plain sight”. Steganography is the art and science of communicating in such a way
that the presence of a message cannot be detected. Simple steganographic techniques have
been in use for hundreds of years, but with the increasing use of files in an electronic format
new techniques for information hiding have become possible.
Figure1.1 shows how information hiding can be broken down into different areas.
Steganography can be used to hide a message intended for later retrieval by a specific
individual or group. In this case the aim is to prevent the message being detected by any other
party.
Figure1.1 Classification of Steganography
Steganography and encryption are both used to ensure data confidentiality. However
the main difference between them is that with encryption anybody can see that both parties
are communicating in secret. Steganography hides the existence of a secret message and in
the best case nobody can see that both parties are communicating in secret. This makes
steganography suitable for some a task for which encryption isn’t, such as copyright marking.
8. Adding encrypted copyright information to a file could be easy to remove but
embedding it within the contents of the file itself can prevent it being easily identified and
removed.
Steganography provides a means of secret communication which cannot be removed
without significantly altering the data in which it is embedded. The embedded data will be
confidential unless an attacker can find a way to detect it.
Steganography or Stego as it is often referred to in the IT community, literally means,
"Covered writing" which is derived from the Greek language. Steganography is defined as
follows, "Steganography is the art and science of communicating in a way which hides the
existence of the communication. In contrast to Cryptography, where the enemy is allowed to
detect, intercept and modify messages without being able to violate certain security premises
guaranteed by a cryptosystem, the goal of Steganography is to hide messages inside other
harmless messages in a way that does not allow any enemy to even detect that there is a
second message present".
In a digital world, Steganography and Cryptography are both intended to protect
information from unwanted parties. Both Steganography and Cryptography are excellent
means by which to accomplish this but neither technology alone is perfect and both can be
broken. It is for this reason that most experts would suggest using both to add multiple layers
of security.
Steganography can be used in a large amount of data formats in the digital world of
today. The most popular data formats used are .bmp, .doc, .gif, .jpeg, .mp3, .txt and .wav.
Mainly because of their popularity on the Internet and the ease of use of the steganographic
tools that use these data formats. These formats are also popular because of the relative ease
by which redundant or noisy data can be removed from them and replaced with a hidden
message. Steganographic technologies are a very important part of the future of Internet
security and privacy on open systems such as the Internet. Steganographic research is
primarily driven by the lack of strength in the cryptographic systems on their own and the
desire to have complete secrecy in an open-systems environment. Many governments have
created laws that either limit the strength of cryptosystems or prohibit them completely. Civil
liberties advocates fight this with the argument that “these limitations are an assault on
privacy”. This is where Steganography comes in. Steganography can be used to hide
9. important data inside another file so that only the parties intended to get the message even
knows a secret message exists. To add multiple layers of security and to help subside the
"crypto versus law" problems previously mentioned, it is a good practice to use Cryptography
and Steganography together. As mentioned earlier, neither Cryptography nor Steganography
are considered "turnkey solutions" to open systems privacy, but using both technologies
together can provide a very acceptable amount of privacy for anyone connecting to and
communicating over these systems.
CHAPTER 2
10. AN ADAPTIVE LSB-OPAP EMPLOYED PIXEL
DOMAIN STEGO TECHNIQUE (ALOS)
To enhance the embedding capacity of image steganography and provide
animperceptible stego-image for human vision, a novel adaptive number of leastsignificant
bits substitution method with private stego-key based on color imageranges are proposed in
this methodology. The new technique embeds binary bit streamin each 8 bit pixel value. The
methodalso verifies that whether the attacker has tried to modify the secret hidden (orstego-
image also) information in the stego-image. The technique embeds thehidden information in
the spatial domain of the cover image and uses simple (Ex-OR operation based) digital
signature using 140-bit key to verify the integrity fromthe stego-image. Besides, the
embedded confidential information can beextracted from stego-images without the assistance
of original images.
2.1 Proposed Methodology
The proposed scheme works on the spatial domain of the cover image and employed
an adaptivenumber of least significant bits substitution in pixels. Variable K-bits insertion
into least significantpart of the pixel gray value is dependent on the private stego-key K1.
Private stego-key consistsof four gray-level ranges that are selected randomly in the range 0-
255. The selected key showsthe four ranges of gray levels and each range substitute different
fixed number of bits into leastsignificant part of the 8-bit gray value of the pixels. After
making a decision of bits insertion into different ranges, Pixel p(x, y) gray value “g” that fall
within the range Ai-Bi is changed by embedding k-message bits of secret information into
new gray value “g’ ”. This new gray value “g’ ”of the pixel may go beyond the range Ai-Bi
that makes problem to extract the correct information at the receiver. Specific gray value
adjustmentmethod is used that make the new gray value “g’ ” fall within the range Ai-Bi.
Confidentiality isprovided by the private stego-key k1 and to provide integrity of the
embedded secret information,140-bit another key K2 is used. Digital signature of the secret
information with the key K2 wereobtained and appended with the information. The whole
message plus signature is embeddedinto the cover image that provides some bit overheads
but used to verify the integrity. At thereceiver key K1 is used to extract the message and key
K2 is used to verify the integrity of themessage.
11. 2.2 Private stego-key generation
Private stego-key K1 play an important role in proposed methodology to provide
security and deciding the adaptive K bits insertion into selected pixel. For a gray scale image
8-bit is used to represent intensity of pixel, so there are only 256 different gray values any
pixel may hold. Different pixels in image may hold different gray values. We may divide the
pixels of images into different groups based on gray ranges. Based on this assumption let four
ranges ofray levels are < A1-B1, A2-B2, A3-B3, A4-B4 > each range starting and ending
value are in8-bits.
2.3 Method to decide Bits insertion in each range
Let the four gray ranges decided by the stego-key are <A1-B1, A2-B2, A3-B3, A4-
B4> andnumber of pixel count from cover image in each range are < N1, N2, N3, N4 >.
Range withmaximum pixel count will hold maximum bits insertion let four bits, second
maximum count willhold three bits insertion and so on. In similar way we decide the bits
extraction from each range. ForExample assume key K1 is 0-64, 65-127, 128-191, 192-255
and let pixel count in eachrange from any image are 34,13238,17116, 35148. Then range first
insert one message bits in thepixel that comes within the range, range second insert two
message bits in the pixel,range thirdinsert three bit in the pixel ,range four insert four bits in
the pixel. In this manner we decide the bits insertion into eachrange.
2.4 LSB substitution
Least significant substitution is an attractive and simple method to embed secret
information intothe cover media and available several versions of it. We employ in propose
scheme adaptive LSBsubstitution method in which adaptive K-bits of secret message
aresubstituted into leastsignificant part of pixel value. Fig.2 shows entire method for K-bits
insertion.
g original value K- zero bits K- msg bits
Modify value g’
12. Fig 2: method for k- bits insertion
To decide arbitrary k-bits insertion into pixel, first we find the range of pixel value and then
findthe number of bits insertion decided by method given in section 2.3 and insert K-message
bitsinto least significant part of pixel using LSB. After embedding the message bits the
changed grayvalue g’ of pixel may go beyond the range.
CHAPTER 3
Pixelvalue in
8 - bits
AND OR
Value in 8 -
bits
K-
LSB’s
13. THE LSB BASED OPTIMUM PIXEL ADJUSTMENT
PROCESS (OPAP)
The Least significant substitution is a simple method to embed secret information into
the cover media. We employ in propose scheme adaptive LSBsubstitution method in which
adaptive K-bits of secret message are substituted into leastsignificant part of pixel value. To
decide arbitrary k-bits insertion into pixel, first we find the range of pixel value and then
findthe number of bits insertion decided by method given in section 2 and insert K-message
bitsinto least significant part of pixel using LSB.
Figure 3.1 shows the whole process.
Fig 3.1 LSB - OPAP
After embedding the message bits the changed grayvalue g’ of pixel may go beyond
the range. To make value within the range, reason is thatreceiver side required to count pixels
to extract message, pixel value adjusting method is appliedto make changed value within
range called as Optimum Pixel Adjustment Process.
After embedding the K-message bits into the pixel gray value g new gray vale g’ may
go outside the range. For example let our range based on key is 0-32. Let the gray value g of
the pixel is 00100000 in binary forms (32 in Decimal), decided K-bits insertion is 3-bits are
K = K+1
14. 111. The pixel new gray value g’ will be 00100111 in binary forms after inserting three bits
(39 in Decimal).
Modified value is outside the range. To make within the range 0-32, K+1 bits of g’ is
changed from 0 to 1 or via- versa and checked again to fall within range if not K+2 bit is
changed and so on until gray value fall within range. For example: 00100111- 00101111-
00111111- 00011111.
15. CHAPTER 4
IMPLEMENTATION OF ALOS: FLOW DIAGRAM
AND ALGORITHM
The algorithms used to implement Adaptive LSB-OPAP stego technique is described
as below:
4.1 Algorithms: Embedding
Input: Cover-image, secret message, keys K1, K2.
Output: Stego-image.
Step1: Read key K1 based on gray-Level ranges.
Step2: Read cover image
Step3: Decide No. of bits insertion into each range described in section 2.3
Step4: Read the secret message and Convert it into bit stream form.
Step5: Read the key K2.
Step6: Find the signature using K2 and append with the message bits.
Step7: For each Pixel
7.1: Find gray value g.
7.2: Decide the K-bits insertion based on gray ranges.
7.3: Find K-message bits and insert using method given in section 2.4
7.4: Decide and adjust new gray Value g’ using method described in Optimum pixel
adjustment process.
7.5: Go to step 7.
Step 8: end
The secret message is first converted into binary bit stream and its digital signature is
calculated using xor structure with the help of key-2 (140 bits), this signature is then
appended into the message and then embedding is done based on LSB substitution method by
key-1, on a cover image in spatial domain. The stego image is then transmitted through the
channel to the authorized receiver side, where the secret data embedded can be extracted
using the shared key.
Figure 4.1 and 4.2 shows the flow diagram for secret message embedding and
extraction along with digital signature respectively.
17. 4.2 Algorithm: Extracting
Input: Stego-image, keys K1, K2;
Output: Secret information;
Step1: Read key K1 based on gray-level ranges.
Step2: Read the stego image.
Step3: Decide No. of bits extraction into each range described in section 2.3.
Step4: For each pixel, extract the K-bits and save into file.
Step5: Read the key K2 and find the signature of bit stream
Step6: Match the signature.
Step7: End
Fig 4.2 Message extractionand integrity check
18. CHAPTER 5
ADVANTAGES & APPLICATIONS OF PROPOSED
SYSTEM
5.1 Advantages
High hiding capacity compared to LSB Substitution technique.
Robust in nature, i.e., highly secure algorithm since two keys (key-1 and key-2) are
used.
We get good quality of the stegoimage.
High water marking level.
Provides maximum possible payload.
Embedded data is imperceptible to the observer.
5.2 Limitations
High computational complexity.
Requires a lot of overhead to hide a relatively bits of information.
This can be overcome by using HIGH SPEED COMPUTERS.
5.3 Applications
In secret communication system.
Military applications.
Hiding and protecting of secret data in industry.
Airlines.
19. CHAPTER 6
EXPERIMENTAL RESULTS AND DISCUSSIONS
In this implementation, Lena and baboon 256 × 256 × 3 colourdigital images have
been taken as coverimages and are tested for various ranges along with different size of secret
messages chosen. The effectiveness of thestego process has been studied by calculating
PSNR for the two digital images in RGB planesand tabulated. First analysis is used to select
the Range for embedding data (in this analysis Range1 is 0-64, 65-127, 128-191, 192-255)
and the results are tabulated in Table-12.3 for various Ranges. From the table we will
understand that Range2 for cover image baboon provides high Payload and Range1 for cover
image baboon provides low payload.
Range
Cover
image
Max bits that can be
embedded (payload)
No of bits embedded
Capacity
(bits/pixel)
PSNR
Range1
Lena 653149
51360 3.2016 44.9412
4768 3.141 55.5705
115360 3.2268 40.8688
Baboon 609524
51360 3.2927 44.7668
4768 3.2 54.8287
115360 3.0352 41.7503
Range2
Lena 693700
51360 3.624 43.494
4768 3.7338 53.4812
115360 3.6078 40.3313
Baboon 700087
51360 3.6488 43.2479
4768 3.7192 53.6941
115360 3.5019 40.2084
Table 6.1 Tabulated result for ALOS technique for secret image
20. Figure 6.1 Experimental result using Range1 for Baboon cover image
The above figure 6.1 shows the input cover image and output stego image and their
respective histograms. The above results are obtained for using Range1. The maximum
payload obtained is 609524 bits, on an average of 3.0352 bits per pixel with the PSNR of
41.7503.
The input cover image
0
200
400
600
The histogram of input cover image
0 100 200
The output stego image
0
200
400
600
800
The histogram of stego image
0 100 200
21. Figure 6.2 Experimental result using Range2 for Lena cover image
The above figure 6.2 shows the input cover image and output stego image and their
respective histograms. The above results are obtained for using Range2. The maximum
payload obtained is 31975 bits, on an average of 3.6078 bits per pixel with the PSNR of
40.3313.
The input cover image
0
200
400
600
800
The histogram of input cover image
0 100 200
The output stego image
0
500
1000
The histogram of stego image
0 100 200
22. CONCLUSION
This novel image steganographic model results in high-capacity embedding/extracting
characteristic based on the Variable-Size LSB substitution. In the embedding part based on
stego-key selected from the gray value range 0-255, it uses pixel value adjusting method to
minimize the embedding error and adaptive 1-4 bits to embed in the pixel to maximize
average capacity per pixel. Using the proposed method, it can be shown that atleastfour
message bits in each pixel can be emebbed, while maintaining the imperceptibility. For the
security requirement, two different ways are proposed to deal with the issue. The major
benefit of supporting these two ways is that the sender can use different stego-keys in
different sessions to increase difficultly of steganalysis on these stego images. Using only the
stego-keys, which is used to count the number of pixel in each range and second 140-bit key
to verify the integrity of the message, the receiver can extract the embedded messages
exactly. Experimental resultsverify that the proposed model is effective and efficient.
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