Secret Data Hiding Scheme with Least Significant Bit Matching Revisited Image Steganography based on Novel E-Coli Bacterial Foraging Optimization Model

2016 ◽  
Vol 6 (7) ◽  
pp. 807
Author(s):  
P. M. Siva Raja ◽  
E. Baburaj
Keyword(s):  
Data Hiding ◽  
Optimization Model ◽  
Image Steganography ◽  
Least Significant Bit ◽  
Secret Data ◽  
Bacterial Foraging Optimization ◽  
E Coli ◽  
Bacterial Foraging

scholarly journals High Capacity Image Steganography using Pixel Value Differencing Method with Data Compression using Neural Network

2019 ◽  
Vol 8 (12) ◽  
pp. 1800-1804
Keyword(s):  
Neural Network ◽  
Data Compression ◽  
Data Hiding ◽  
Image Steganography ◽  
Data Embedding ◽  
Least Significant Bit ◽  
Secret Data ◽  
Stego Image ◽  
Compression Technique ◽  
Hiding Capacity

The Digital Market Is Rapidly Growing Day By Day. So, Data Hiding Is Going To Increase Its Importance. Information Can Be Hidden In Different Embedding Mediums, Known As Carriers By Using Steganography Techniques. The Carriers Are Different Multimedia Medium Such As Images, Audio Files, Video Files, And Text Files .There Are Several Techniques Present To Achieve Data Hiding Like Least Significant Bit Insertion Method And Transform Domain Technique. The Data Hidden Capacity Inside The Cover Image Totally Depends On The Properties Of The Image Like Number Of Noisy Pixels. Data Compression Provides To Hide Large Amount Of Secret Data To Increase The Capacity And The Image Steganography Based On Any Neural Network Provides That The Size And Quality Of The Stego-Image Remains Unaltered After Data Embedding. In This Paper We Propose A New Method Combined With Data Compression Along With Data Embedding Technique And After Embedding To Maintain The Quality The Communication Channel Use The Neural Network. The Compression Technique Increase The Data Hiding Capacity And The Use Of Neural Network Maintain The Flow Of Data Processing Signal

Optimal Placement of Distributed Generation Using Bacterial Foraging Optimization Algorithm

2015 ◽  
Vol 781 ◽  
pp. 329-332
Author(s):  
Parichart Sodsri ◽  
Bongkoj Sookananta ◽  
Mongkol Pusayatanont
Keyword(s):  
Distributed Generation ◽  
Optimization Algorithm ◽  
Distribution System ◽  
Optimal Placement ◽  
Bacterial Foraging Optimization ◽  
E Coli ◽  
Bacterial Foraging ◽  
Bus Voltage ◽  
Bacterial Foraging Optimization Algorithm

This paper presents the determination of the optimal distributed generation (DG) placement using bacterial foraging optimization algorithm (BFOA). The BFO mimics the seeking-nutrient behavior of the E. coli bacteria. It is utilized here to find the location and size of the DG installation in radial distribution system in order to obtain minimum system losses. The operation constraints include bus voltage limits, distribution line thermal limits, system power balance and generation power limits. The algorithm is tested on the IEEE 33 bus system. The result shows that the algorithm could be used as an alternative to the other techniques and improvement of the algorithm is required for acceleration and better accuracy of the calculation.

A new dynamic bacterial foraging optimization and its application on model reduction

2015 ◽  
Vol 06 (02) ◽  
pp. 1550018
Author(s):  
Shenli Wu ◽  
Sun'an Wang ◽  
Xiaohu Li
Keyword(s):  
Model Reduction ◽  
Optimization Problems ◽  
Clonal Selection ◽  
Poor Performance ◽  
Step Size ◽  
Bacterial Foraging Optimization ◽  
Bacterial Populations ◽  
E Coli ◽  
Bacterial Foraging ◽  
Complex Optimization

Inspired by the foraging behavior of E. coli bacteria, bacterial foraging optimization (BFO) has emerged as a powerful technique for solving optimization problems. However, BFO shows poor performance on complex and high-dimensional optimization problems. In order to improve the performance of BFO, a new dynamic bacterial foraging optimization based on clonal selection (DBFO-CS) is proposed. Instead of fixed step size in the chemotaxis operator, a new piecewise strategy adjusts the step size dynamically by regulatory factor in order to balance between exploration and exploitation during optimization process, which can improve convergence speed. Furthermore, reproduction operator based on clonal selection can add excellent genes to bacterial populations in order to improve bacterial natural selection and help good individuals to be protected, which can enhance convergence precision. Then, a set of benchmark functions have been used to test the proposed algorithm. The results show that DBFO-CS offers significant improvements than BFO on convergence, accuracy and robustness. A complex optimization problem of model reduction on stable and unstable linear systems based on DBFO-CS is presented. Results show that the proposed algorithm can efficiently approximate the systems.

scholarly journals Testing of Image Steganography with use of LSB and DCT Techniques

2019 ◽  
Vol 8 (10) ◽  
pp. 3694-3697
Keyword(s):  
High Speed ◽  
Signal To Noise Ratio ◽  
Data Communication ◽  
Image Steganography ◽  
Digital Data ◽  
Data Detection ◽  
Least Significant Bit ◽  
Secret Data ◽  
Text Information ◽  
Audio Video

In this growing internet world, secret data communication is increasing day by day. There are various methods to communicate secretly. Steganography is one of those techniques in which data is concealed within cover data such that it cannot get detected. Steganography is usually used today on pcs where digital data is the high-speed distribution channels for carriers and networks. Steganography is the skill of understanding of unnoticeable activity at intervals. Steganalysis is the science of concealed data detection. Steganography of data which is of any form like images, audio, video or text information is done by various techniques. Image steganography is done by various technique. Least Significant Bit (LSB) with XORing and Discrete Cosine Transform (DCT) are used to test the image steganography. Images are converted to grey scale to get better accuracy. Results are tested with mean square error (MSE) and peak signal-to-noise ratio (PSNR) values.

scholarly journals Design and Implementation of Lifting Based Wavelet and Adaptive LSB Steganography to Secret Data Sharing Through Image on FPGA

2018 ◽  
Vol 8 (03) ◽  
Author(s):  
Kokila B. Padeppagol ◽  
Sandhya Rani M H
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Image Data ◽  
Image Steganography ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Least Significant Bit ◽  
Secret Data ◽  
Secret Image ◽  
Design And Implementation

Image steganography is an art of hiding images secretly within another image. There are several ways of performing image steganography; one among them is the spatial approach.The most popular spatial domain approach of image steganography is the Least Significant Bit (LSB) method, which hides the secret image pixel information in the LSB of the cover image pixel information. In this paper a LSB based steganography approach is used to design hardware architecture for the Image steganography. The Discrete Wavelet Transform (DWT) is used here to transform the cover image into higher and lower wavelet coefficients and use these coefficients in hiding the secret image. the design also includes encryption of secret image data, to provide a higher level of security to the secret image. The steganography system involving the stegno module and a decode module is designed here. The design was simulated, synthesized and implemented on Artix -7 FPGA. The operation hiding and retrieving images was successfully verified through simulations.

scholarly journals Image Steganography using Improved Lsb-Mapping Technique with Enhanced Recovery Speed

2019 ◽  
Vol 8 (4) ◽  
pp. 11473-11478
Keyword(s):  
Data Hiding ◽  
Enhanced Recovery ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Cover Image ◽  
Mapping Technique ◽  
Secret Data ◽  
Logical Function ◽  
Hiding Capacity ◽  
Carrier Image

In recent days, for sending secret messages, we require secure internet. Image steganography is considered as the eminent tool for data hiding which provides better security for the data transmitted over internet. In the proposed work, the payload data is embedded using improved LSB-mapping technique. In this approach, two bits from each pixel of carrier image are considered for mapping and addition. Two bits of payload data can be embedded in one cover image pixel hence enhanced the hiding capacity. A logical function on addition is applied on 1st and 2nd bits of cover image pixel, and a mapping table is constructed which gives solution for data hiding and extraction. Simple addition function on stego pixel is performed to extract payload data hence increases the recovery speed. Here the secret data is not directly embedded but instead mapped and added with a number using modulo-4 strategy. Hence the payload data hidden using proposed approach provide more security and it can resist against regular LSB decoding approaches. The proposed work is implemented and tested for several gray scale as well as color images and compared with respect to parameters like peak signal to noise ratio and MSE. The proposed technique gives better results when compared and histogram of cover and stego images are also compared.

scholarly journals Viewing Direction Based LSB Data Hiding in 360° Videos

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1527
Author(s):  
Dang Ninh Tran ◽  
Hans-Jürgen Zepernick ◽  
Thi My Chinh Chu
Keyword(s):  
Data Hiding ◽  
Gaussian Mixture Models ◽  
Visual Quality ◽  
Structural Similarity ◽  
Gaussian Mixture ◽  
Experimental Results ◽  
Weight Functions ◽  
Least Significant Bit ◽  
Secret Data ◽  
The Impact

In this paper, we propose a viewing direction based least significant bit (LSB) data hiding method for 360° videos. The distributions of viewing direction frequency for latitude and longitude are used to control the amount of secret data to be hidden at the latitude, longitude, or both latitude and longitude of 360° videos. Normalized Gaussian mixture models mimicking the viewing behavior of humans are formulated to define data hiding weight functions for latitude, longitude, and both latitude and longitude. On this basis, analytical expressions for the capacity offered by the proposed method to hide secret data in 360° cover videos are derived. Numerical results for the capacity using different numbers of bit planes and popular 360° video resolutions for data hiding are provided. The fidelity of the proposed method is assessed in terms of the peak signal-to-noise ratio (PSNR), weighted-to-spherically uniform PSNR (WS-PSNR), and non-content-based perceptual PSNR (NCP-PSNR). The experimental results illustrate that NCP-PSNR returns the highest fidelity because it gives lower weights to the impact of LSB data hiding on fidelity outside the front regions near the equator. The visual quality of the proposed method as perceived by humans is assessed using the structural similarity (SSIM) index and the non-content-based perceptual SSIM (NCP-SSIM) index. The experimental results show that both SSIM-based metrics are able to account for the spatial perceptual information of different scenes while the PSNR-based fidelity metrics cannot exploit this information. Furthermore, NCP-SSIM reflects much better the impact of the proposed method on visual quality with respect to viewing directions compared to SSIM.

scholarly journals Image Steganography combined with Cryptography

2013 ◽  
Vol 9 (1) ◽  
pp. 976-984 ◽  
Author(s):  
Vijaya Lakshmi Paruchuri ◽  
Dr.R. Sridevi ◽  
K.S. SadaSiva Rao
Keyword(s):  
Image Steganography ◽  
Secret Message ◽  
Secret Key ◽  
Least Significant Bit ◽  
Secret Data ◽  
Encrypted Image ◽  
Hidden Data ◽  
Audio Files ◽  
Lsb Technique ◽  
The Right

Steganography is the science of invisible communication. Apart from the sender and intended recipient no one suspects the existence of the message. Using Steganography, information can be hidden in various mediums known as carriers. The carriers can be images, audio files, video files and text files. Image Steganography is a technique of using an image file as a carrier. Cryptography protects the information by applying the encryption and decryption techniques, so that the secret message can be understood only by the right person.This paper proposes a method, which combines the techniques of Steganography and cryptography, to hide the secret data in an image. In the first phase, the sender will embed the secret data in an image by using the Least Significant Bit (LSB) technique. The embedded image will be encrypted by using an encryption algorithm. At final, the encrypted image will be decrypted and the hidden data will be retrieved by supplying the valid secret key by the receiver. The process includes the phases of Data embedding, Image Encryption and recovery of both original image and secret data from the encrypted image.

scholarly journals Cooperative Bacterial Foraging Optimization

2009 ◽  
Vol 2009 ◽  
pp. 1-17 ◽  
Author(s):  
Hanning Chen ◽  
Yunlong Zhu ◽  
Kunyuan Hu
Keyword(s):  
Marked Improvement ◽  
Optimization Problems ◽  
Social Foraging ◽  
Decomposition Level ◽  
Bacterial Foraging Optimization ◽  
E Coli ◽  
Space Decomposition ◽  
Bacterial Foraging ◽  
The Social ◽  
Complex Optimization

Bacterial Foraging Optimization (BFO) is a novel optimization algorithm based on the social foraging behavior ofE. colibacteria. This paper presents a variation on the original BFO algorithm, namely, the Cooperative Bacterial Foraging Optimization (CBFO), which significantly improve the original BFO in solving complex optimization problems. This significant improvement is achieved by applying two cooperative approaches to the original BFO, namely, the serial heterogeneous cooperation on the implicit space decomposition level and the serial heterogeneous cooperation on the hybrid space decomposition level. The experiments compare the performance of two CBFO variants with the original BFO, the standard PSO and a real-coded GA on four widely used benchmark functions. The new method shows a marked improvement in performance over the original BFO and appears to be comparable with the PSO and GA.

scholarly journals A Novel and Innovative Approach for Image Steganography with Chaos

2018 ◽  
Vol 11 (1) ◽  
pp. 263
Author(s):  
Krishnaveni N ◽  
Sudhakar P
Keyword(s):  
Logistic Map ◽  
Image Steganography ◽  
Integer Wavelet Transform ◽  
Embedding Capacity ◽  
Least Significant Bit ◽  
Secret Data ◽  
Logistic Mapping ◽  
High Embedding Capacity ◽  
Integer Wavelet ◽  
Chaotic Logistic Map

Steganography is the art/technique of hiding message data inside a carrier file in such a way that unauthorized or unsolicited personnel is not capable of detecting the presence of data inside the carrier file. The Proposed Method provides improved security and improved high embedding capacity image steganography through the usage of Integer Wavelet Transform (IWT) and Chaotic Logistic map. Least Significant Bit technique is used to replace the bits in the coefficient of detail band. The proposed method offers lossless and unnoticeable change in the image steganography. In this paper we focus on both cryptography and steganography for better confidentiality, security and robustness. We find that the proposed algorithm has a better CMPSNR (Chaotic Logistic mapping) value averaging close to 74 after embedding the secret data, while the existing algorithms have values of around 65.

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