scholarly journals Steganography: Securing Message in wireless network

2013 ◽  
Vol 4 (3) ◽  
pp. 797-801 ◽  
Author(s):  
A H M Kamal
Keyword(s):  
Wireless Network ◽  
True Positive Rate ◽  
Modulus Function ◽  
Secret Message ◽  
Least Significant Bit ◽  
Lsb Matching ◽  
Survey Paper ◽  
Binary Space Partition ◽  
Space Partition ◽  
Noise Margin

Steganography is the process of hiding a secret message with in a cover medium. However eavesdropper may guess the embedding algorithm like least significant bit (LSB) replacement of Chan et al, 2004; Wang et al, 2001; Wu et al, 2005, LSB matching of Mielikainen, 2006, addition and/or subtraction of Andead wastfield, 2001; F. Huang et al in 2011, Exploiting Modification Direction by Zhang and Wang, 2006, Binary Space Partition by Tsai and Wang, 2007, modulus function of Chin et al, 2011 and thus can apply the respective extraction method to detect the secret message. So challenges lies in the methodologies of embedding message. Capacity, security and robustness are the services to be demanded by users. Again the true-positive rate of secret message detection by eavesdropper should be lessened by applying firm technique. Thirdly operating domain should be less sensitive to the noise, margin level of losses or alteration of data while communicating through unguided medium like wireless network, sensor network and cellular network. This paper will briefly discuss the steganographic methods and their experimental results explained in the survey paper of Niels Provos and Peter Honeyman to hide and seek message. Finally the proposed results and the directions for future works are addressed.

Image and audio steganography based on indirect LSB

2021 ◽  
Vol 48 (4) ◽  
Author(s):  
Zainab N. Sultani ◽  
◽  
Ban N. Dhannoon ◽  
Keyword(s):  
Information Hiding ◽  
Experimental Results ◽  
Secret Message ◽  
Text File ◽  
Least Significant Bit ◽  
Audio Steganography

Hiding the presence of data during communication has become a pressing concern in this overly digitalized world as a consequence of illegitimate access. These concerns have led to cryptography and steganography techniques as methods for securing data. This paper presents a modified information hiding technique based on an indirect least significant bit. Instead of saving each bit of the secret message in the least significant bit (LSB) of the cover media, each bit of the secret message is compared to a mask bit in the cover media. The result is saved in the cover media’s LSB. In this paper, two steganography schemas are designed in which the cover media are image and audio, while the secret message is a text file. A simple encryption technique is used to transform the secret message into an unreadable format before the hiding process begins. The experimental results indicate that the proposed algorithm achieves promising performance

Pixel Prediction-Based Image Steganography by Support Vector Neural Network

2020 ◽  
Author(s):  
Reshma V K ◽  
Vinod Kumar R S
Keyword(s):  
Neural Network ◽  
Medical Image ◽  
Medical Information ◽  
Similarity Index ◽  
Image Steganography ◽  
Secret Message ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Least Significant Bit ◽  
Prediction Scheme

Abstract Securing the privacy of the medical information through the image steganography process has gained more research interest nowadays to protect the privacy of the patient. In the existing works, least significant bit (LSB) replacement strategy was most popularly used to hide the sensitive contents. Here, every pixel was replaced for achieving higher privacy, but it increased the complexity. This work introduces a novel pixel prediction scheme-based image steganography to overcome the complexity issues prevailing in the existing works. In the proposed pixel prediction scheme, the support vector neural network (SVNN) classifier is utilized for the construction of a prediction map, which identifies the suitable pixels for the embedding process. Then, in the embedding phase, wavelet coefficients are extracted from the medical image based on discrete wavelet transform (DWT) and embedding strength, and the secret message is embedded into the HL wavelet band. Finally, the secret message is extracted from the medical image on applying the DWT. The experimentation of the proposed pixel prediction scheme is done by utilizing the medical images from the BRATS database. The proposed pixel prediction scheme has achieved high performance with the values of 48.558 dB, 0.50009 and 0.9879 for the peak signal to noise ratio (PSNR), Structural Similarity Index (SSIM) and correlation factor, respectively.

scholarly journals Improved Binary Space Partition merging

2008 ◽  
Vol 40 (12) ◽  
pp. 1113-1120 ◽  
Author(s):  
Mikola Lysenko ◽  
Roshan D’Souza ◽  
Ching-Kuan Shene
Keyword(s):  
Binary Space Partition ◽  
Space Partition

PARALLEL SOLID MODELING USING BSP DATAFLOW

2008 ◽  
Vol 18 (05) ◽  
pp. 441-467 ◽  
Author(s):  
GIORGIO SCORZELLI ◽  
ALBERTO PAOLUZZI ◽  
VALERIO PASCUCCI
Keyword(s):  
Geometric Modeling ◽  
Large Scale ◽  
Solid Modeling ◽  
Complex Objects ◽  
Dataflow Graph ◽  
Object Space ◽  
Binary Space Partition ◽  
Space Partition ◽  
Hidden Surface Removal ◽  
Computational Processes

We introduce a parallel approach to geometric modeling of complex objects and scenes, combining a dataflow streaming of BSP trees with a partition of the object space into independent portions, to be evaluated in parallel with minimal interprocess communication. Binary Space Partition (BSP) is a space index used in graphics for hidden-surface removal and animation. We use BSP trees with fuzzy leaves as a progressive representation of solid meshes. Our approach is implemented as a dataflow with processes that progress concurrently, where each refinement of the input to a process is mapped instantly to a refinement of the output, so that the result is also a stream of progressive refinements. This framework allows for progressive generation of complex geometric parts and large-scale assemblies. We have adapted several graphics techniques, including BSP, boundary polygons, CSG, splines and subdivision methods, to fit into our dataflow graph, where four types of processes produce, transform, combineor consume mesh cells. This approach is scalable over different kinds of HPC hardware and different number of computing nodes, by way of the decomposition of the object space and of the distribution of computational processes. Compiling a generative geometric expression into a dataflow graph is well suited to SMP machines, whereas a space decomposition into independent portions fits well with computing clusters and grids.

scholarly journals Steganographic Scheme based on Message-Cover matching

2018 ◽  
Vol 8 (5) ◽  
pp. 3594
Author(s):  
Youssef Taouil ◽  
El Bachir Ameur
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Secret Message ◽  
Discrete Wavelet ◽  
Large Set ◽  
Integer Part ◽  
Least Significant Bit ◽  
Secret Data ◽  
Trade Off ◽  
Good Trade

Steganography is one of the techniques that enter into the field of information   security, it is the art of dissimulating data into digital files in an imperceptible way that does not arise the suspicion. In this paper, a steganographic method based on the Faber-Schauder discrete wavelet transform is proposed. The embedding of the secret data is performed in Least Significant Bit (LSB) of the integer part of the wavelet coefficients. The secret message is decomposed into pairs of bits, then each pair is transformed into another pair based on a permutation that allows to obtain the most matches possible between the message and the LSB of the coefficients. To assess the performance of the proposed method, experiments were carried out on a large set of images, and a comparison to prior works is accomplished. Results show a good level of imperceptibility and a good trade-off imperceptibility-capacity compared to literature.

scholarly journals Crypto-Steganographic Method to Protect Secret Messages

2021 ◽  
Vol 10 (12) ◽  
pp. 46-61
Author(s):  
Mohamad Tariq Barakat ◽  
Rushdi Abu Zneit ◽  
Ziad A. Alqadi
Keyword(s):  
Digital Image ◽  
Color Image ◽  
Color Images ◽  
Secret Message ◽  
Security Level ◽  
Least Significant Bit ◽  
Simple Method ◽  
Private Key ◽  
Message Length ◽  
Digital Color Images

Multiple methods are used to hide secret messages in digital color images, and the most important and most common is the least significant bit (LSB) method. The LSB method is a known and exposed method, and anyone with programming experience can retrieve the secret message embedded in the digital image. In this paper research we will add some enhancements to improve the security level of LSB method to protect the embedded secret message from being hacked. A simple method of secret message cryptography will be used to encrypt the secret message before bedding it using LSB method. The method will be based on using color image as an image_key; this image_key will be resized to generate the needed secret private key used to encrypt-decrypt secret message. The length and the contents of the generated private key will dynamically change depending on the message length and the selected image_key. The selected image_key will be kept in secret without transmission and will be known only by the sender and receiver and it can be changed any time when needed. The proposed crypto_steganographic method will be implemented to show how it will increase the level o secret message protection.

scholarly journals A Technique for Secure Communication Using Message Dependent Steganography

2012 ◽  
pp. 122-126
Author(s):  
Gandharba Swain ◽  
Dodda Ravi Kumar ◽  
Anita Pradhan ◽  
Saroj Kumar Lenka
Keyword(s):  
Secure Communication ◽  
Secret Message ◽  
Least Significant Bit ◽  
Secret Information ◽  
Cipher Text ◽  
Carrier Image ◽  
Substitution Cipher

In this paper we present a technique for secure communication between two parties Alice and Bob. We use both cryptography and steganography. We take image as the carrier to use steganography. By using our own substitution cipher called two square reverse we encrypt the secret information. Then the cipher text of the secret information is embedded into the carrier image in LSB (least significant bit) minus one position of some selected bytes. The byte selection is done depending on the bit pattern of the secret information. Thus the embedding locations are dependent on the secret message. So the intruder will face difficulties to locate the bits. After embedding the resultant image will be sent to the receiver, the receiver will apply the reverse operation what the sender has done and get the secret information.

scholarly journals Hiding Data in Color Image Using Least Significant Bits of Blue Sector

2018 ◽  
Vol 31 (2) ◽  
pp. 193 ◽  
Author(s):  
Hussein L. Hussein
Keyword(s):  
Color Image ◽  
Cover Image ◽  
Secret Message ◽  
Mapping Technique ◽  
Least Significant Bit ◽  
Blue Sector ◽  
Powerful Technique ◽  
Secret Communication ◽  
Least Significant Bits

Concealing the existence of secret hidden message inside a cover object is known as steganography, which is a powerful technique. We can provide a secret communication between sender and receiver using Steganography. In this paper, the main goal is for hiding secret message into the pixels using Least Significant Bit (LSB) of blue sector of the cover image. Therefore, the objective is by mapping technique presenting a model for hiding text in an image. In the model for proposing the secret message, convert text to binary also the covering (image) is divided into its three original colors, Red, Green and Blue (RGB) , use the Blue sector convert it to binary,  hide two bits from the message in  two bits of the least significant bits of blue sector of the image.

scholarly journals Hungarian-Puzzled Text with Dynamic Quadratic Embedding Steganography

2017 ◽  
Vol 7 (2) ◽  
pp. 799
Author(s):  
Ebrahim Alrashed ◽  
Suood Suood Alroomi
Keyword(s):  
Exponential Growth ◽  
Assignment Problem ◽  
Ease Of Use ◽  
Secret Message ◽  
Least Significant Bit ◽  
Digital Medium ◽  
Stego Image ◽  
High Quality ◽  
Hungarian Algorithm ◽  
Embedding Technique

Least-Significant-Bit (LSB) is one of the popular and frequently used steganography techniques to hide a secret message in a digital medium. Its popularity is due to its simplicity in implementation and ease of use. However, such simplicity comes with vulnerabilities. An embedded secret message using the traditional LSB insertion is easily decodable when the stego image is suspected to be hiding a secret message.  In this paper, we propose a novel secure and high quality LSB embedding technique. The security of the embedded payload is employed through introducing a novel quadratic embedding sequence. The embedding technique is also text dependent and has non-bounded inputs, making the possibilities of decoding infinite. Due to the exponential growth of and quadratic embedding, a novel cyclic technique is also introduced for the sequence that goes beyond the limits of the cover medium. The proposed method also aims to reduce the noise arising from embedding the secret message by reducing bits changed. This is done by partitioning the cover medium and the secret message into N partitions and artificially creating an assignment problem based on bit change criteria. The assignment problem will be solved using the Hungarian algorithm that will puzzle the secret message partition for an overall least bit change.

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