scholarly journals Information Hiding using LSB Technique based on Developed PSO Algorithm

2018 ◽  
Vol 8 (2) ◽  
pp. 1156 ◽  
Author(s):  
Wisam Abed Shukur ◽  
Khalid Kadhim Jabbar
Keyword(s):  
Information Hiding ◽  
Particle Swarm Optimization Algorithm ◽  
Signal To Noise Ratio ◽  
Pso Algorithm ◽  
Search Space ◽  
Secret Message ◽  
Stego Image ◽  
Carrier Medium ◽  
Lsb Technique ◽  
Lsb Substitution

<p>Generally, The sending process of secret information via the transmission channel or any carrier medium is not secured. For this reason, the techniques of information hiding are needed. Therefore, steganography must take place before transmission. To embed a secret message at optimal positions of the cover image under spatial domain, using the developed particle swarm optimization algorithm (Dev.-PSO) to do that purpose in this paper based on Least Significant Bits (LSB) using LSB substitution. The main aim of (Dev. -PSO) algorithm is determining an optimal paths to reach a required goals in the specified search space based on disposal of them, using (Dev.-PSO) algorithm produces the paths of a required goals with most efficient and speed. An agents population is used in determining process of a required goals at search space for solving of problem. The (Dev.-PSO) algorithm is applied to different images; the number of an image which used in the experiments in this paper is three. For all used images, the Peak Signal to Noise Ratio (PSNR) value is computed. Finally, the PSNR value of the stego-A that obtained from blue sub-band colo is equal (44.87) dB, while the stego-B is equal (44.45) dB, and the PSNR value for the stego-C is (43.97)dB, while the vlue of MSE that obtained from the same color sub-bans is (0.00989), stego-B equal to (0.01869), and stego-C is (0.02041). Furthermore, our proposed method has ability to survive the quality for the stego image befor and after hiding stage or under intended attack that used in the existing paper such as Gaussian noise, and salt &amp; pepper noise.</p>

scholarly journals An novel architecture for information hiding using HMAC-MD5

2013 ◽  
Vol 2 (2) ◽  
pp. 134 ◽  
Author(s):  
Agilandeeswari Loganathan ◽  
Brindha Krishnamoorthy ◽  
Stiffy Sunny ◽  
Muralibabu Kumaravel
Keyword(s):  
Data Security ◽  
Information Hiding ◽  
Secret Message ◽  
Digital Form ◽  
Secret Data ◽  
Sensitive Data ◽  
Current Discussion ◽  
Payload Capacity ◽  
Lsb Technique ◽  
Embedded Image

Communication in digital form has become the part of day todays lifestyle, in certain moment communication is made secret to avoid others from knowing the information. By providing security to the sensitive data it is ensured that the users data is protected from viewing and accessing by others. In the current discussion about data security, Steganographic algorithm using two mediums has been discussed that involves image based encryption and converting to word file. The stage involving image based encryption uses HMAC-MD5 algorithm along with LSB steganography. LSB technique scatters the secret data which have to be protected over the entire image. Convert the embedded image in word file, so that the secret message is made unavailable to others who try to obtain the file. This method provides greater payload capacity along with higher image fidelity and thus make the proposed system is more robust against attacks.

Reversible data hiding method based on pixel expansion and homomorphic encryption

2020 ◽  
Vol 39 (3) ◽  
pp. 2977-2990
Author(s):  
R. Anushiadevi ◽  
Padmapriya Praveenkumar ◽  
John Bosco Balaguru Rayappan ◽  
Rengarajan Amirtharajan
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Signal To Noise Ratio ◽  
Homomorphic Encryption ◽  
Secret Message ◽  
Pixel Expansion ◽  
Stego Image ◽  
Encrypted Image ◽  
Location Map

Digital image steganography algorithms usually suffer from a lossy restoration of the cover content after extraction of a secret message. When a cover object and confidential information are both utilised, the reversible property of the cover is inevitable. With this objective, several reversible data hiding (RDH) algorithms are available in the literature. Conversely, because both are diametrically related parameters, existing RDH algorithms focus on either a good embedding capacity (EC) or better stego-image quality. In this paper, a pixel expansion reversible data hiding (PE-RDH) method with a high EC and good stego-image quality are proposed. The proposed PE-RDH method was based on three typical RDH schemes, namely difference expansion, histogram shifting, and pixel value ordering. The PE-RDH method has an average EC of 0.75 bpp, with an average peak signal-to-noise ratio (PSNR) of 30.89 dB. It offers 100% recovery of the original image and confidential hidden messages. To protect secret as well as cover the proposed PE-RDH is also implemented on the encrypted image by using homomorphic encryption. The strength of the proposed method on the encrypted image was verified based on a comparison with several existing methods, and the approach achieved better results than these methods in terms of its EC, location map size and imperceptibility of directly decrypted images.

scholarly journals High-Capacity Image Steganography with Minimum Modified Bits Based on Data Mapping and LSB Substitution

2018 ◽  
Vol 8 (11) ◽  
pp. 2199 ◽  
Author(s):  
Abdul Zakaria ◽  
Mehdi Hussain ◽  
Ainuddin Wahab ◽  
Mohd Idris ◽  
Norli Abdullah ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
High Capacity ◽  
Visual Quality ◽  
Data Mapping ◽  
Embedding Capacity ◽  
Secret Data ◽  
Stego Image ◽  
Mapping Strategy ◽  
Lsb Substitution

Steganography is the art and practice of communication using hidden messages. The least significant bits (LSB) based method is the well-known type of steganography in the spatial domain. Usually, achieving the larger embedding capacity in LSB-based methods requires a large number of LSB bits modification which indirectly reduces the visual quality of stego-image and increases the risk of steganalysis detection attacks. In this study, we propose a novel steganography method with data mapping strategy which can reduce the number of bits modification per pixel. In the proposed method, four secret data bits are mapped with the four most significant bits of a cover pixel. Furthermore, the only two LSBs of a pixel are modified to indicate the mapping strategy. Experimental results show that the proposed method is able to achieve 3.48% larger embedding capacity while enhancing the visual quality (i.e., peak signal to noise ratio (PSNR) 3.73 dB) and reducing the modification of 0.76 bits per pixel. Moreover, the proposed method provides security against basic Regular and Singular groups (RS) steganalysis and histogram steganalysis detection attacks.

scholarly journals Least Significant Braille Method in Steganography Using Digital Image Media For Security Message

2017 ◽  
Vol 6 (1) ◽  
pp. 15-20
Author(s):  
Megah Mulya ◽  
Zikry Sugiwa
Keyword(s):  
Digital Image ◽  
Signal To Noise Ratio ◽  
Human Vision ◽  
Secret Message ◽  
Signal To Noise ◽  
Stego Image ◽  
Resistance Level ◽  
Noise Ratio

Confidentiality of the message or the information is the most important and essential.  It is very influential on the party who has the valuable message when they want to exchange messages on others.  To keep the message is not known to others, the necessary security on the message.  Steganography is one technique for providing security to the message.  Steganography is a technique to hide messages in a medium, such as pictures, sounds and video.  Steganographic technique used in this study is the Least Significant Braille (LSBraille).  This technique makes use of human vision in the message on the bit value was not significant.  This study focuses on how much resistance level stego image to various image processes and measure results accuracy Peak Signal to Noise Ratio (PSNR).  From the result of the insertion of a secret message, that the level of resistance stego image is not resistant to digital image processing.  The result of the calculation of PSNR value obtained from experiments on all data samples between 51-73 db.

scholarly journals Information Hiding Based on Histogram and Pixel Pattern

2017 ◽  
Author(s):  
Ari Moesriami Barmawi ◽  
Deden Pradeka
Keyword(s):  
Information Hiding ◽  
Information Exchange ◽  
High Capacity ◽  
Cover Image ◽  
Secret Message ◽  
Embedding Capacity ◽  
Stego Image ◽  
Image Histogram ◽  
Pixel Value ◽  
Value Changes

Recently, information exchange using internet is increasing, such that information security is necessary for securing confidential information because it is possible to eavesdrop the information. There are several methods for securing the exchanged information such as was proposed by Rejani et al. Rejani’s method can be noiseless in low capacity but noisy in high capacity. In the case of high capacity, it will raise suspicion. This research proposed a method based on histogram and pixel pattern for keeping the stego image noiseless while still keeping the capacity high. Secret information can be embedded into the cover by evaluating the histogram and map the characters used in the secret message to the consecutive intensity in the cover image histogram. The map of the characters is sent to the recipient securely. Using the proposed method there is no pixel value changes during the embedding process. Based on the result of the experiments, it is shown that in noiseless condition, the proposed method has higher embedding capacity than Rejani’s especially when using cover image with sizes larger than 128 × 128. Thus, in noiseless condition the embedding capacity using the proposed method is higher than Rejani’s method in noiseless condition.  

scholarly journals Video Steganography Using LSB Substitution and Sobel Edge Detection

2018 ◽  
Vol 11 (2) ◽  
pp. 67-73
Author(s):  
Ashty M. Aaref
Keyword(s):  
Signal To Noise Ratio ◽  
English Text ◽  
Secret Message ◽  
Data Embedding ◽  
Edge Point ◽  
Video Steganography ◽  
The Mean ◽  
Sobel Edge Detection ◽  
Lsb Substitution

The procedure that involves the in closure of information without altering its intuitive standard is called data embedding. In this paper the secret message (English text) is hidden in the edge of the frames of the .AVI video without changing the details of frames. MATLAB R2013a is utilized to execute this algorithm. The secret message was embedded in the frames 38,39,40,41 and 42 and the reason of selecting those frames is that these frames have sufficient edge point details in them. High embedding and superior quality of encoded secret messages have been accomplished by this design. Additionally, in this project the cover frame image is represented by a 120 frames size 120* 160, and the secret message has been represented with a message comprised of 300 characters Both Peak Signal to Noise Ratio (PSNR) and the Mean Square Error (MSE) have been taken into consideration while analyzing the suggested method as we calculated both PSNR and MSE between the cover frames and the embedded ones. The results obtained were objectively good as the PSNR value ranges from 74.5293dB to 75.9123 dB

scholarly journals Data Hiding and Retrieval Method Using LSB Substitution Algorithm

2021 ◽  
pp. 267-279
Author(s):  
Asoke Nath ◽  
Soham Mondal ◽  
Raj Deb ◽  
Akash Das
Keyword(s):  
Public Communication ◽  
Secret Message ◽  
The Internet ◽  
Stego Image ◽  
Substitution Method ◽  
Retrieval Method ◽  
Secret Information ◽  
Other Information ◽  
Weak Points ◽  
Lsb Substitution

Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information. Many different carrier ?le formats can be used, but digital images are the most popular because of their frequency on the Internet. For hiding secret information in images, there exists a large variety of steganography techniques some are more complex than others and all of them have respective strong and weak points. Different applications have different requirements of the steganography technique used. For example, some applications may require absolute invisibility of the secret information, while others require a larger secret message to be hidden. This project hides the message within the image. This project uses LSB Substitution method to hide the secret message inside the image. Sender select the cover image with the secret message ?le (which can be of any format) and hide it into the image, it help to generate the secure stego image. The stego image is sent to the destination with the help of private or public communication network. On the other side the receiver downloads the stego image and using the software retrieve the secret text hidden in the stego image.

scholarly journals PERBAIKAN ALGORITMA STEGANOGRAFI TEKNIK LEAST SIGNIFICANT BITS UNTUK APLIKASI KEAMANAN DATA

2018 ◽  
Vol 3 (1) ◽  
pp. 27-32
Author(s):  
Tika Erna Putri ◽  
Muhammad Rifqi Al Fauzan ◽  
Prima Asmara Sejati
Keyword(s):  
Digital Media ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Third Party ◽  
Security Level ◽  
Least Significant Bit ◽  
Stego Image ◽  
Security Issues ◽  
Squared Error ◽  
Lsb Technique

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.

scholarly journals POLAR PARTICLE SWARM OPTIMIZATION ALGORITHM FOR SOLVING OPTIMAL REACTIVE POWER PROBLEM

2018 ◽  
Vol 6 (6) ◽  
pp. 335-345
Author(s):  
K. Lenin
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm Optimization Algorithm ◽  
Reactive Power ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Search Space ◽  
Swarm Optimization ◽  
Polar Function ◽  
Standard Particle Swarm Optimization ◽  
Power Problem

This paper presents Polar Particle Swarm optimization (PPSO) algorithm for solving optimal reactive power problem. The standard Particle Swarm Optimization (PSO) algorithm is an innovative evolutionary algorithm in which each particle studies its own previous best solution and the group’s previous best to optimize problems. In the proposed PPSO algorithm that enhances the behaviour of PSO and avoids the local minima problem by using a polar function to search for more points in the search space in order to evaluate the efficiency of proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms. Simulation results demonstrate good performance of the Polar Particle Swarm optimization (PPSO) algorithm in solving an optimal reactive power problem.

scholarly journals Digital FIR Filter Design by PSO and its variants Attractive and Repulsive PSO(ARPSO) & Craziness based PSO(CRPSO)

2021 ◽  
Vol 9 (6) ◽  
pp. 136-141
Author(s):  
Zain Ali ◽  
Bharat Lal Harijan ◽  
Tayab Din Memon ◽  
Nazmus Naf ◽  
Ubed-u-Rahman Memon
Keyword(s):  
Video Processing ◽  
Particle Swarm Optimization Algorithm ◽  
Optimization Problems ◽  
Filter Design ◽  
Pso Algorithm ◽  
Search Space ◽  
Fir Filter ◽  
Unique Approach ◽  
Fir Filter Design ◽  
Better Than

Digital filters play a major role in signal processing that are employed in many applications such as in control systems, audio or video processing systems, noise reduction applications and different systems for communication. In this regard, FIR filters are employed because of frequency stability and linearity in their phase response. FIR filter design requires multi-modal optimization problems. Therefore, PSO (Particle Swarm Optimization) algorithm and its variants are more adaptable techniques based upon particles’ population in the search space and a great option for designing FIR filter. PSO and its different variants improve the solution characteristic by providing a unique approach for updating the velocity and position of the swarm. An optimized set of filter coefficient is produced by PSO and its variant algorithms which gives the optimized results in passband and stopband. In this research paper, Digital FIR filter is effectively designed by using PSO Algorithm and its two variants ARPSO and CRPSO in MATLAB. The outcomes prove that the filter design technique using CRPSO is better than filter design by PM algorithm. PSO and ARPSO Algorithms in the context of frequency spectrum and RMS error.

Sign in / Sign up

Export Citation Format

Share Document