Least Significant Bit Algorithm Research Articles

Message Hiding Using the Least Significant Bit Method with Shifting Hill Cipher Security

Technological developments go hand in hand with advances in digital messaging. In protecting the confidentiality of the message, it is necessary to double secure the data. This security can be done with a combination of steganography and cryptographic techniques. Steganography algorithm which is a technique for hiding messages well, one of which is Least Significant Bit (LSB). The LSB algorithm is a simple method because it only converts the value of the last bit in a message with the inserted message bit, which is a convenience of the LSB algorithm, but it becomes vulnerable to message theft attacks if not combined with other algorithms for security. So it is necessary to increase security. This research developed a combination method of LSB algorithm for steganography technique with Hill Cipher algorithm for cryptographic technique, Hill Cipher was developed with shifting (shifting) 2 (two) characters. With the development of this method, hackers will find it difficult to crack messages, and is expected to improve the performance of the algorithm in affecting image quality and travel time in running the algorithm. The results of this study will be tested using several evaluation tools MSE, PSNR, BER, CER, AE, and Entropy. With the development of this method, hackers will find it difficult to decipher messages, and from the results of this experiment has been able to improve the performance of the algorithm in maintaining image quality and can shorten travel time in running the algorithm.

Secret Communication Using Multi-Image Steganography with Face Recognition and OTP System

Abstract: Our Proposed system is to develop a Web operation for hiding information in any image train to ensure the safety of the exchange of data between different military parties and give better security during communication transmission. We use the LSB fashion. The proposed approach uses a steganography algorithm to bed data in the image lines for military operations. For security purposes, we used modules face Recognition fashion with the AES algorithm for Strong Security purposes. And we use the cover channel fashion as an information-hiding fashion that can be exploited by a process to transfer information in a manner that violates the system security programs. Image steganography is the main aspect of information caching where the ciphertext is bedded into an image called a cover image which is coming to insolvable for the interferers to see with their naked eyes. The retired information can be any textbook, images, audio, or indeed videos inside a cover image. The abstract description ofMulti-image Steganography is that the secret law is divided into multiple corridors and is etched into multiple cover images. So we proposed two image steganography ideas to make it veritably grueling for the hackers to conceal the data. This paper proposes the Least significant bit( LSB) fashion of Steganography and the Advanced Encryption Standard( AES) fashion of Cryptography to make a safe and secure system. Then the sender and the receiver use the same key to encrypt and decipher the data which is popularly nominated a symmetric crucial Keywords AES Algorithm, LSB Algorithm, and Steganography.

Implementation of the Least Significant Bit Method for Hiding Text in Digital Images

To speed up the process of sending secret messages, we need a medium for small messages that can still guarantee the confidentiality of the messages they contain. GIF (Graphics Interchange Format) is an image format that is one of the most commonly used formats on the web because of its small size and for encrypting the text that is sent. Encryption is carried out at the time of delivery by converting the original data into confidential data, while decryption is carried out at the time of receipt by converting the confidential data into original data. The most common way to hide messages is to use the Least Significant Bit (LSB). This research has succeeded in implementing the LSB algorithm to solve steganography on digital images in GIF format optimally

Steganography a Technique to Hide Information within an Image

Steganography is the science and art of secret communication between two parties that seek to conceal the content of their messages. It is a technology that embeds information into cover photos without losing information after embedding. Steganography is the technique and method of hiding a message so that no one but the sender and receiver will suspect how the message survived. This article compares two different techniques. The first technique uses the least significant bit (LSB) without encryption or compression. Now in the second method, the encrypted message is first encrypted and then the least significant bit is used. The image is then transformed into the frequency domain using a Discrete Cosine Transform (DCT). The LSB algorithm is applied in the local domain where the image parts corresponding to the payload are embedded in the least significant parts of the overlay image and the image is embedded in the least significant parts of the overlay image to generate a steganographic image. The DCT algorithm is appliedin the frequency domain and transforms from the steganographic image domain to the spatial domain where the image title is interpolated to the least significant parts of the image. This white paper mainly provides an overview of steganography requirements benefits and related technologies. This white paper shows which steganographic methods are most effective for which requirements are met and which applications are most compatible with which steganographic methods.

The Implementation of Improved Advanced Encryption Standard and Least Significant Bit for Securing Messages in Images

Security and confidentiality are essential aspects needed in the process of exchanging messages. Maintaining the message's security and confidentiality can be done by encrypting the message with cryptographic techniques to protect the message. However, the encrypted message (ciphertext) usually raises suspicion from eavesdroppers so that they try to unravel the contents of the message or damage the contents of the message or prevent the message from reaching the intended recipient. To avoid eavesdroppers' suspicion of encrypted messages, after encryption, the ciphertext can then be inserted into an image using steganography techniques so that eavesdroppers do not know whether there is a secret message in an image. In this research, the authors use the Improved AES-128 (Advanced Encryption Standard) Algorithm to encrypt messages and LSB (Least Significant Bit) Algorithm to insert ciphertext into an image. Where the AES Algorithm Improvement is made by adding a sending and receiving applications ID to modify the Key Schedule process, with modifications to the Key Schedule process, messages can only be read on the original recipient's cellphone by entering the correct key. The results of this study show that eavesdroppers do not easily know the existence of the ciphertext, besides that even if the eavesdroppers get the ciphertext and know the encryption key, the message remains unreadable on their cellphone because the ID of the application sending or receiving the message has changed.

PERBANDINGAN DAN KOMBINASI KINERJA ALGORITMA LEAST SIGNIFICANT BIT DENGAN PIXEL VALUE DIFFERENCING PADA STEGANOGRAFI CITRA WARNA

One of the most common problems in this digitalization era is data security issues, such as being compromised by digital data. Actually, there are many ways to protect digital data, one of which is by using steganography techniques. Where the steganography technique is a technique for inserting a secret message into an image media. In this study, we will discuss how the performance of two teganographic methods, namely Least Significant Bit (LSB) and Pixel Value Differencing (PVD) and how the results if the two methods are combined in implementing color image steganography. To determine the quality of the method studied, MSE, PSNR, and SSIM were used as testing methods. As a result, the PVD algorithm on the red tifanny layer image obtained an MSE value of 0.051, PSNR 60,974, and SSIM 0.998. For the LSB algorithm, the flax image in the green layer obtained MSE values of 0.0039, PSNR 72.218, and SSIM 1.000. Finally, the combination algorithm between PVD and LSB on tifanny's image in the red layer obtained an MSE value of 0.054, PSNR 60,734, and SSIM 0.998.

Smart Home Privacy Protection Based on the Improved LSB Information Hiding

Smart home is an emerging form of the Internet of Things (IoT), enabling people to enjoy a convenient and intelligent life. The data generated by smart home devices are transmitted through the public channel, which is not secure enough, so the secret data in smart home are easily intercepted by malicious adversaries. In order to solve this problem, this paper proposes a smart home privacy protection method combining DES encryption and the improved Least Significant Bit (LSB) information hiding algorithm, changing the practice of directly exposing smart home secret information to the Internet, first, using Data Encryption Standard (DES) encryption to encrypt the smart home information and second, the improved LSB information hiding algorithm is used to hide the ciphertext, so that the adversary cannot detect the smart home secret information. The goal of the scheme is to provide a double protection for the secure transmission of the smart home secret information. If an attacker wants to carry out an attack, it has to break through at least two defense lines, which seems impossible to do. Experiment results show that the improved LSB algorithm is more robust than the existing algorithms, and it is very safe. Therefore, the scheme proposed in this paper is very practical for protecting the smart home secret information.

Local Features-Based Watermarking for Image Security in Social Media

The last decade shows an explosion of using social media, which raises several challenges related to the security of personal files including images. These challenges include modifying, illegal copying, identity fraud, copyright protection and ownership of images. Traditional digital watermarking techniques embed digital information inside another digital information without affecting the visual quality for security purposes. In this paper, we propose a hybrid digital watermarking and image processing approach to improve the image security level. Specifically, variants of the widely used Least-Significant Bit (LSB) watermarking technique are merged with a blob detection algorithm to embed information into the boundary pixels of the largest blob of a digital image. The proposed algorithms are tested using several experiments and techniques, which are followed by uploading the watermarked images into a social media site to evaluate the probability of extracting the embedding watermarks. The results show that the proposed approaches outperform the traditional LSB algorithm in terms of time, evaluation criteria and the percentage of pixels that have changed.

Implementation Of Least Significant Bit (LSB) Algorithm For Data Security In Digital Imagery

In this study, a software was built that can insert text messages into image files (steganography) and steganalisis or detect the presence or absence of secret messages in an image. Imagery is the most commonly used medium for inserting secret messages, as it can hide messages very well and is widely available. The built software implements steganalisis with the Least Significant Bit (LSB) algorithm which is the most widely used message insertion algorithm. Steganlysis software is built using LSB algorithms to perform insertion and extract insertion messages on image files. The LSB algorithm in this study used the microsoft Visual Basic 6.0 programming language tools. Based on the software tests conducted, it can be seen that the software can run well on insertion and detect the presence or absence of secret messages on image files.

A NEW IMPERCEPTIBLE STEGANOGRAPHY METHOD FOR GRAYSCALE IMAGES

A standard Least Significant Bit (LSB) algorithm changes average 50% of the least significant bits of an image. This causes approximately a 0.2% distortion on a grayscale image. Therefore, the application of LSB on non-sharp grayscale images causes too much noise that can be easily detected by the human visual system. In addition; when the image is scanned pixel by pixel, hidden message can be easily read by unauthorized persons. A robust and imperceptible block-based LSB steganography method is developed in this study. First, cover image is divided into blocks, then median geometric mean and arithmetic mean of each block is calculated to select blocks those contain less detail of the image. Method has an advantage of calculating data load capacity of image before embedding process. Proposed method also makes it difficult for unauthorized people to detect hidden messages. Performance of the method is measured by mathematical methods such as MSE, PSNR and SSIM. The method achieved structured similarity score over 0.9999% on four test images, indicating a 20-fold better result than the standard LSB algorithm.

Hiding and Data Safety Techniques in Bmp Image with LSB and RPrime RSA Algorithm

Image is a form of visual data or information that is often used today. Sending data or information can be done in various ways and anyone. However, not all contents of existing information are public. It is not uncommon that information is misused by irresponsible parties. For this reason, security is needed for confidential information. This image security can be done with Steganography Technique. Steganography technique is a method for hiding information in an image. The method used is the LSB (Least Significant Bit) method. Where every bit lowest in the image media bytes will be replaced with the message bits that will be inserted. The bit used is the last bit of the RGB binary. The goal is that the message sent by the sender cannot be known by a third party, and can arrive safely to the recipient of the message. To make the confidentiality of messages more secure, it is necessary to hide the existence of messages to overcome the weaknesses of the LSB method used, so the authors combine them with the RSA RPrime algorithm (Rivest Shamir Adleman) for the encryption and decryption process. The security of the RSA RPrime algorithm lies in the level of difficulty in factoring non prime numbers into prime factors. The longer the key bits, the more difficult it is to solve because of the difficulty of factoring these two very large numbers. The results showed the test using a document file 2.93 MB with cover image size of 5760 x 3840 pixels, where in the larger the file inserted, then the time of encryption and decryption process is also long.

Analysis of Least Significant Bit Method Using Sequential Encoding-Decoding in Steganography Digital Image

The method of steganography commonly used to hide data or information is Least Significant Bit (LSB) method. One of the relevant research is LSB using sequential Encoding - Decoding by David Pipkorn and Preston Weisbrot. In this research, an analysis of the LSB method using Sequential Encoding - Decoding by doing some testing. The tests are on the aspect of message security using tools StegSpy and enhanced LSB algorithm, testing on image quality by calculating the Peak Signal to Noise Ratio (PSNR) value and see the image histogram, testing on robustness of message by doing some image processing operations on stego image, like cropping, rotating, and etc, and then testing on capacity to check size of cover image and stego image and calculates the maximum size of data that can be hidden. From the testing process, we know that there are deficiencies in the aspects of security, robustness and capacity of a message. And then in this research we try to change the location of messages that are hidden in the image bits, which previous research used the 8th bit of each bytes, changed to the 7th bit. To be able to correct deficiencies in the security aspect. After repairing and testing like before, obtained better results in the security aspect. This can be seen from the image of the enhanced LSB algorithm process, the message is not detected, but unfortunately the image quality is reduced, with the low PSNR value generated.

Hiding data in images using steganography techniques with compression algorithms

Steganography is the science and art of secret communication between two sides that attempt to hide the content of the message. It is the science of embedding information into the cover image without causing a loss in the cover image after embedding.Steganography is the art and technology of writing hidden messages in such a manner that no person, apart from the sender and supposed recipient, suspects the lifestyles of the message. It is gaining huge attention these days as it does now not attract attention to its information's existence. In this paper, a comparison of two different techniques is given. The first technique used Least Significant Bit (LSB) with no encryption and no compression. In the second technique, the secret message is encrypted first then LSB technique is applied. Moreover, Discrete Cosine Transform (DCT) is used to transform the image into the frequency domain. The LSB algorithm is implemented in spatial domain in which the payload bits are inserted into the least significant bits of cover image to develop the stego-image while DCT algorithm is implemented in frequency domain in which the stego-image is transformed from spatial domain to the frequency domain and the payload bits are inserted into the frequency components of the cover image.The performance of these two techniques is evaluated on the basis of the parameters MSE and PSNR.

Analysis on Combination of Watermarking Algorithm: Modified Least Significant Bit Algorithm with Least Significant Bit+1

To protect someone’s copyright on digital media such as digital image, watermarking technique can be used, which is a technique to insert copyright marks into digital media. The algorithms that commonly used in the watermark insertion is the Least Significant Bit (LSB). But there is deficiency in LSB algorithm. LSB algorithm requires one byte image pixel to insert one bit watermark. The more byte pixels are inserted, the higher the difference between watermarked image with the original image. Embedded watermark can also easily be known because it is definitely placed on the LSB bits of the pixel image. From these problems, in this research we analyze the combination of two watermarking algorithms: Modified Least Significant Bit (MLSB) with Least Significant Bit (LSB+1). MLSB have the advantage in compressing the watermark to be inserted from eight bit/character into five bit/character. LSB+1 algorithm will cover the deficiency of MLSB algorithm, which the location of the watermark bit is easy to be discovered. Added in this research, the watermark bit had inserted in random image pixel. The Combined algorithm tested by using five image that have different sizes and dimensions, which each of the image inserted by text watermark that have different length. The purpose is to find the value of these three comparison parameters: Mean Squared Error value (MSE), the size of the result image and processing time. It concluded that for the three parameters, the combined algorithm of MLSB-LSB+1 have done better than the LSB+1algorithm but slightly worse than the MLSB algorithm. This happens due to MLSBLSB+1 besides inheriting the advantages of each algorithm, also inherited deficiency of the LSB+1 algorithm which is because of the insertion is in the one bit before the least significant bit of the image pixel, the value of the pixel is greater for two point(in decimal).

Aplikasi Penyembunyian Data Rahasia Ke Citra Digital dengan menggunakan Metode Rivest Shamir Adleman dan Least Significant Bit

Steganography is the science of art and science to make hidden messages in a certain way so that other people besides the sender and recipient will realize there is a hidden message. Cryptography is science and art to learn about processing and securing messages safely. This study will discuss the combination of the Rivest Shamir Adleman (RSA) and Least Significant Bit (LSB) methods on how to hide a secret message in a digital image. A text message before being inserted into a digital image is first encrypted with the RSA Algorithm, the results of the encryption are inserted digital imagery with LSB Algorithm. The length of the text message depends on the size of the container media. Applications designed using Microsoft Visual Basic 2008 also provide interfaces for generating randomly needed keys. Applications can be used to hide secret messages in digital images where the color changes of input images with results are not clearly visible.

Image in Image Steganography based on modified Advanced Encryption Standard and Lest Significant Bit Algorithms

Because the big grown of the digital market and the growing demand for protection to data and information which transmitted through the Internet. Steganography is the art of embedding, hiding information into different digital media, it was the main reason to increase its importance in the exponential development of the secret communication of computer and digital cloud users over the internet. There are a lot of techniques and different ways to achieve hiding data. Usually, the data embedding is obtained in communication such as image, text, voice or any multimedia content for copyright and also in military communication for authentication and many other different purposes. In this paper, we protected the information in two ways: Encryption and Steganography. The basic idea is to present a method that encrypted the message firstly by using The AES (Advanced Encryption Standard) it is a symmetric-key encryption each of these ciphers it has 128-bit the size to block, and size keys of 128, 192 and 256 bits. Secondly, hide that encrypted message in color cover image in the Least Significant Bit (LSB) to image’s frame with (.bmp, .jpg) extensions. Our scheme is to enhance the ability of LSB algorithm to include the storage of information and images encoded and intangible sense of human vision. That two methods to increased together the security attend any attack.

PERBAIKAN ALGORITMA STEGANOGRAFI TEKNIK LEAST SIGNIFICANT BITS UNTUK APLIKASI KEAMANAN DATA

Security issues have become major problem in the field of data communications, specifically in the data transmission through the internet. One of the solutions is to hide the messages through a digital media so the attention of the attacker or third party can be avoided, this method is known as steganography. In this research, we use images as digital media. We modify the Least Significant Bit (LSB) which is the most commonly used technique in steganography. Unfortunately LSB has poor security level since it is already widely known technique. Therefore, it is important to modify the algorithm of LSB to ensure its security aspect. An improvement to LSB technique is suggested by selecting only odd pixels and ignoring even pixels in the implementation of steganography. We successfully implement the modified LSB algorithm by using RBG image and grayscale image as steganography media. Mean Squared Error (MSE) and Peak Signal-to-noise Ratio (PSNR) are employed to evaluate the stego-image quality. Our calculations show that the modified LSB algorithm provides better results than the conventional LSB. The conventional LSB algorithm gives 1.98 10-5 for MSE and 95.20893 dB for PSNR calculations, while the modified LSB gives 1. 80 10-5 and 95.6101 dB for MSE and PSNR, respectively.

A Capable System for Hiding Image in an Image

In this paper, we have proposed a new method by for hiding an image using steganographic called GanKan. This method is based on Least Significant Bit (LSB) replacement and can be used for 24 bit color image capable of producing a secret-embedded image. This paper clearly showed that this GanKan new method is better than LSB technique for 8 bit color image and 24 bit color image. Firstly LSB method for both 8 bit and 24 bit color image are described and then the GanKan method for 24 bit color image, compare their result by calculating Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Root Mean Square Error (RMSE) and histogram analysis. LSB Algorithm embedded MSB of secret image into LSB of cover image. In the case of 24 bit color image two methods are described. In first method, last 2 LSB of each plane (RGB) of cover image, is replaced by 2 MSB of secret image. In the second method, last LSB of each red plane is replaced by first MSB of secret image, last 2 LSB of each green plane by next 2 MSB of secret image and then last 3 LSB of blue plane is replaced by next 3 MSB of secret image. This means that total 6 bits of secret image can be hided in 24 bit color image. Experimental results showed that the embedded-image is visually indistinguishable from the original cover-image in the case of 24 bit.

Increasing the hiding capacity in image steganography using Braille code

Least significant bit (LSB) insertion steganography is a one of the most widely used methods for implementing covert data channels in image file exchanges. This popularity comes from its simplicity in implementation and low computational complexity of the algorithm moreover the primary reason being low image distortion. Many researchers try to increase the embedding capacity of LSB algorithm by increasing the layers of the image by keeping the image with minimal distortion effects. This paper introduces a new approach for embedding the data within the images using Braille code and bit-slicing technique. It will be shown that this unique steganography method has minimal visual distortion affects while also hiding the message with a secure and small code.

Sequential Multiple LSB methods and real-time data hiding: variations for Visual Cryptography ciphers

In this paper, a general model approach of real-time data hiding and watermarking for image, video and audio communications is proposed. The aim is the development of security robustness variations and data-rate (capacity) extensions of Steganography fast schemes for RT (real time) or NRT (near real time) image, video and audio media communication and data hiding, with no significant distortion of the medium. Additionally, this paper includes the proposal of specific case models such as Steganography of the total of Visual Cryptography schemes of black and white images. Influenced by our survey on Spatial Domain Steganography techniques such as Multiple LSB (Least Significant Bit) algorithm, Matrix Embedding and Parity Coding, a new potential method is introduced called in brief from now on SMLSB (Sequential Multiple LSB) method comparing other respective methods and algorithms researched, SMLSB is a different approach on real-time and non-real-time data hiding, which gives an advantage of robustness, while it provides various modes of the method depending on the requirements. Also the method can be used for the specific occasion of Visual Cryptography Ciphers’ Steganography.