scholarly journals Security and imperceptibility improving of image steganography using pixel allocation and random function techniques

2022 ◽  
Vol 12 (1) ◽  
pp. 694
Author(s):  
Noor Alhuda F. Abbas ◽  
Nida Abdulredha ◽  
Raed Khalid Ibrahim ◽  
Adnan Hussein Ali
Keyword(s):  
Information Security ◽  
Digital Image ◽  
Random Function ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Huffman Coding ◽  
Signal To Noise ◽  
Secret Data ◽  
Exchange Of Information ◽  
Information And Communication

Information security is one of the main aspects of processes and methodologies in the technical age of information and communication. The security of information should be a key priority in the secret exchange of information between two parties. In order to ensure the security of information, there are some strategies that are used, and they include steganography and cryptography. An effective digital image-steganographic method based on odd/even pixel allocation and random function to increase the security and imperceptibility has been improved. This lately developed outline has been verified for increasing the security and imperceptibility to determine the existent problems. Huffman coding has been used to modify secret data prior embedding stage; this modified equivalent secret data that prevent the secret data from attackers to increase the secret data capacities. The main objective of our scheme is to boost the peak-signal-to-noise-ratio (PSNR) of the stego cover and stop against any attack. The size of the secret data also increases. The results confirm good PSNR values in addition of these findings confirmed the proposed method eligibility.

scholarly journals Digital Image Steganography Using Bit Flipping

2018 ◽  
Vol 18 (1) ◽  
pp. 69-80 ◽  
Author(s):  
Aditya Kumar Sahu ◽  
Gandharba Swain ◽  
E. Suresh Babu
Keyword(s):  
Digital Image ◽  
Quality Index ◽  
Signal To Noise Ratio ◽  
The State ◽  
Image Steganography ◽  
Original Image ◽  
Signal To Noise ◽  
Secret Data ◽  
Hiding Capacity ◽  
State Of Art

Abstract This article proposes bit flipping method to conceal secret data in the original image. Here a block consists of 2 pixels and thereby flipping one or two LSBs of the pixels to hide secret information in it. It exists in two variants. Variant-1 and Variant-2 both use 7th and 8th bit of a pixel to conceal the secret data. Variant-1 hides 3 bits per a pair of pixels and the Variant-2 hides 4 bits per a pair of pixels. Our proposed method notably raises the capacity as well as bits per pixel that can be hidden in the image compared to existing bit flipping method. The image steganographic parameters such as, Peak Signal to Noise Ratio (PSNR), hiding capacity, and the Quality Index (Q.I) of the proposed techniques has been compared with the results of the existing bit flipping technique and some of the state of art article.

scholarly journals Notice of Retraction Digital Image Steganography Using Bit Flipping

2018 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
Aditya Kumar Sahu ◽  
Gandharba Swain
Keyword(s):  
Digital Image ◽  
Quality Index ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Expert Committee ◽  
Original Image ◽  
Signal To Noise ◽  
Secret Data ◽  
Hiding Capacity ◽  
Secret Information

<p><strong>Notice of Retraction</strong><br /><br />-----------------------------------------------------------------------<br />After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IAES's Publication Principles.<br /><br />We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.<br /><br />The presenting author of this paper has the option to appeal this decision by contacting [email protected].<br /><br />-----------------------------------------------------------------------</p><p>This article proposes bit flipping method to conceal secret data in the original image. Here a section consists of 2 pixels and there by flipping one or two LSBs of the pixels to hide secret information in it. It exists in 2 variants. The variant-1 and variant-2 both use 7<sup>th</sup> and 8<sup>th</sup> bit to conceal the secret data. Variant-1 hides 3 bits per a pair of pixels and the variant-2 hides 4 bits per a pair of pixels. Our proposed method notably raises the capacity as well as bits per pixel that can be hidden in the image compared to existing bit flipping method. The image steganographic parameters such as, peak signal to noise ratio (PSNR), hiding capacity, and the quality index of the proposed techniques has been compared with the existing bit flipping technique</p>

Multilevel Secure Digital Image Steganography Framework Using Random Function and Advanced Encryption Standard

2019 ◽  
Vol 16 (11) ◽  
pp. 4812-4825
Author(s):  
Mohsin N. Srayyih Almaliki
Keyword(s):  
Image Quality ◽  
Random Function ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Secret Message ◽  
Least Significant Bit ◽  
Signal To Noise ◽  
Stego Image ◽  
Preparation Phase ◽  
Noise Ratio

One of the crucial aspects of processes and methodologies in the information and communication technology era is the security of information. The security of information should be a key priority in the secret exchange of information between two parties. In order to ensure the security of information, there are some strategies which are used, and they include steganography and cryptography. With cryptography, the secret message is converted into unintelligible text, but the existence of the secret message is noticed, nonetheless, steganography involves hiding the secret message in a way that its presence cannot be noticed. In this paper, a new secure image steganography framework which is known as an adaptive stego key LSB (ASK-LSB) framework is proposed. The construction of the proposed framework was carried out in four phases with the aim of improving the data-hiding algorithm in cover images by using capacity, image quality, and security. To achieve this, the Peak Signal-to-Noise Ratio (PSNR) of the steganography framework was maintained. The four phases began with the image preparation phase, followed by the secret message preparation phase, embedding phase and finally extraction phase. The secure image steganography framework that is proposed in this study is based on a new adaptive of least significant bit substitution method, combination random function, and encryption method. In the proposed work, the secret bits are inserted directly or inversely, thereby enhancing the imperceptibility and complexity of the process of embedding. Results from the experiment reveal that the algorithm has better image quality index, peak signal-to-noise ratio, and payload used in the evaluation of the stego image.

scholarly journals Two Stage Steganography on Compressed and Encrypted Message

2021 ◽  
Vol 15 ◽  
pp. 494-498
Author(s):  
Kamal Jadidy Aval ◽  
Masumeh Damrudi
Keyword(s):  
Signal To Noise Ratio ◽  
Lossless Compression ◽  
Quality Parameters ◽  
Huffman Coding ◽  
Mean Square ◽  
Least Significant Bit ◽  
Signal To Noise ◽  
Secret Data ◽  
Two Stage ◽  
Unauthorized Access

Security of confidential information in the insecure era of information transmission (Internet) is still one of the most important challenges of the day. The combination of cryptography and steganography increases the security of embedded data to avoid from unauthorized access. Furthermore, compression of secret data reduces the size of transmitted message. In addition to compression and encryption, in this paper, two stage steganography is employed to enhance the security. In the proposed approach, the Huffman coding as lossless compression, the Blowfish, DES, 3DES, AES, and RSA as cryptography algorithms and LSB (Least significant Bit) as steganography technique are employed with enhancement of security by two stage steganography. The results are analyzed through quality parameters including MSE (Mean Square Error) and PSNR (Peak Signal to Noise Ratio), and histogram of images.

Efficient Steganography Algorithm Based On DCT And Entropy Thresholding Technique

2018 ◽  
Vol 8 (1) ◽  
pp. 45
Author(s):  
Satvir Singh
Keyword(s):  
Relative Entropy ◽  
Experimental Work ◽  
Random Function ◽  
Signal To Noise Ratio ◽  
Binary Sequence ◽  
Threshold Value ◽  
Absolute Difference ◽  
Secret Message ◽  
Signal To Noise ◽  
Confidential Information

Steganography is the special art of hidding important and confidential information in appropriate multimedia carrier. It also restrict the detection of  hidden messages. In this paper we proposes steganographic method based on dct and entropy thresholding technique. The steganographic algorithm uses random function in order to select block of the image where the elements of the binary sequence of a secret message will be inserted. Insertion takes place at the lower frequency  AC coefficients of the  block. Before we insert the secret  message. Image under goes dc transformations after insertion of the secret message we apply inverse dc transformations. Secret message will only be inserted into a particular block if  entropy value of that particular block is greater then threshold value of the entropy and if block is selected by the random function. In  Experimental work we calculated the peak signal to noise ratio(PSNR), Absolute difference , Relative entropy. Proposed algorithm give high value of PSNR  and low value of Absolute difference which clearly indicate level of distortion in image due to insertion of secret message is reduced. Also value of  relative entropy is close to zero which clearly indicate proposed algorithm is sufficiently secure. 

Retinal Digital Image Quality Improvement as A Diabetes Retinopatic Disease Detection Effort

2020 ◽  
Vol 4 (2) ◽  
pp. 53-60
Author(s):  
Latifah Listyalina ◽  
Yudianingsih Yudianingsih ◽  
Dhimas Arief Dharmawan
Keyword(s):  
Image Processing ◽  
Diabetic Retinopathy ◽  
Image Quality ◽  
Digital Image ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Vital Role ◽  
Retinal Images ◽  
Signal To Noise ◽  
Noise Ratio

Image processing is a technical term useful for modifying images in various ways. In medicine, image processing has a vital role. One example of images in the medical world, namely retinal images, can be obtained from a fundus camera. The retina image is useful in the detection of diabetic retinopathy. In general, direct observation of diabetic retinopathy is conducted by a doctor on the retinal image. The weakness of this method is the slow handling of the disease. For this reason, a computer system is required to help doctors detect diabetes retinopathy quickly and accurately. This system involves a series of digital image processing techniques that can process retinal images into good quality images. In this research, a method to improve the quality of retinal images was designed by comparing the methods for adjusting histogram equalization, contrast stretching, and increasing brightness. The performance of the three methods was evaluated using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Signal to Noise Ratio (SNR). Low MSE values and high PSNR and SNR values indicated that the image had good quality. The results of the study revealed that the image was the best to use, as evidenced by the lowest MSE values and the highest SNR and PSNR values compared to other techniques. It indicated that adaptive histogram equalization techniques could improve image quality while maintaining its information.

scholarly journals An Image Steganography Algorithm using Fractional Discrete Wavelet Transform with Advanced Encryption System

2020 ◽  
Vol 9 (5) ◽  
pp. 541-546
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Mean Square Error ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Discrete Wavelet ◽  
Mean Square ◽  
Signal To Noise ◽  
Noise Ratio

The research constitutes a distinctive technique of steganography of image. The procedure used for the study is Fractional Random Wavelet Transform (FRWT). The contrast between wavelet transform and the aforementioned FRWT is that it comprises of all the benefits and features of the wavelet transform but with additional highlights like randomness and partial fractional value put up into it. As a consequence of the fractional value and the randomness, the algorithm will give power and a rise in the surveillance layers for steganography. The stegano image will be acquired after administrating the algorithm which contains not only the coated image but also the concealed image. Despite the overlapping of two images, any diminution in the grade of the image is not perceived. Through this steganographic process, we endeavor for expansion in surveillance and magnitude as well. After running the algorithm, various variables like Mean Square Error (MSE) and Peak Signal to Noise ratio (PSNR) are deliberated. Through the intended algorithm, a rise in the power and imperceptibility is perceived and it can also support diverse modification such as scaling, translation and rotation with algorithms which previously prevailed. The irrefutable outcome demonstrated that the algorithm which is being suggested is indeed efficacious.

Learning Aided Digital Image Compression Technique for Medical Application

2016 ◽  
pp. 400-422
Author(s):  
Kandarpa Kumar Sarma
Keyword(s):  
Image Compression ◽  
Digital Image ◽  
Signal To Noise Ratio ◽  
Medical Application ◽  
Learning Systems ◽  
Signal To Noise ◽  
Compression Technique ◽  
Compressed Images ◽  
Digital Image Compression ◽  
Efficiency And Reliability

The explosive growths in data exchanges have necessitated the development of new methods of image compression including use of learning based techniques. The learning based systems aids proper compression and retrieval of the image segments. Learning systems like. Artificial Neural Networks (ANN) have established their efficiency and reliability in achieving image compression. In this work, two approaches to use ANNs in Feed Forward (FF) form and another based on Self Organizing Feature Map (SOFM) is proposed for digital image compression. The image to be compressed is first decomposed into smaller blocks and passed to FFANN and SOFM networks for generation of codebooks. The compressed images are reconstructed using a composite block formed by a FFANN and a Discrete Cosine Transform (DCT) based compression-decompression system. Mean Square Error (MSE), Compression ratio (CR) and Peak Signal-to-Noise Ratio (PSNR) are used to evaluate the performance of the system.

Digital Image Steganography

2017 ◽  
pp. 324-346 ◽  
Author(s):  
Chitra A. Dhawale ◽  
Naveen D. Jambhekar
Keyword(s):  
Communication Network ◽  
Performance Analysis ◽  
Information Security ◽  
Digital Image ◽  
Data Communication ◽  
Image Steganography ◽  
Digital Data ◽  
Confidential Information ◽  
Unauthorized Access ◽  
Data Communication Network

Digital data transmitted over the insecure communication can be prone to attacks. Intruders try various attacks to unauthorized access of the confidential information. The Steganography is such as security system that provide the protection to the images, text and other type of data digitally transferred through the data communication network. This chapter elaborates the basics of Digital Image Steganographic techniques from ancient era to digital edge, types of images used for the steganography, payload used for the steganography, various attacks and different algorithms that can provide the information security. The performance analysis of the various Digital Image Steganographic algorithms are discussed. The current applications and their necessities are discussed in this chapter.

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