scholarly journals Optimal Image Based Information Hiding with One-dimensional Chaotic Systems and Dynamic Programming

2022 ◽  
Vol 19 (1) ◽  
Author(s):  
Yinglei Song ◽  
Jia Song ◽  
Junfeng Qu
Keyword(s):  
Dynamic Programming ◽  
Information Hiding ◽  
Signal To Noise Ratio ◽  
Cover Image ◽  
Dynamic Programming Method ◽  
Stego Image ◽  
One Dimensional ◽  
Other Information ◽  
The Difference ◽  
Two Stages

Information hiding is a technology aimed at the secure hiding of important information into digital documents or media. In this paper, a new approach is proposed for the secure hiding of information into gray scale images. The hiding is performed in two stages. In the first stage, the binary bits in the sequence of information are shuffled and encoded with a set of integer keys and a system of one-dimensional logistic mappings. In the second stage, the resulting sequence is embedded into the gray values of selected pixels in the given image. A dynamic programming method is utilized to select the pixels that minimize the difference between a cover image and the corresponding stego image. Experiments show that this approach outperforms other information hiding methods by 13.1% in Peak Signal to Noise Ratio (PSNR) on average and reduces the difference between a stego image and its cover image to 0 in some cases.

scholarly journals An Advanced Reversible Data Hiding Algorithm Using Local Similarity, Curved Surface Characteristics, and Edge Characteristics in Images

2020 ◽  
Vol 10 (3) ◽  
pp. 836 ◽  
Author(s):  
Soo-Mok Jung ◽  
Byung-Won On
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Image Watermarking ◽  
Surface Characteristics ◽  
Cover Image ◽  
Curved Surface ◽  
Local Similarity ◽  
Stego Image ◽  
Confidential Data ◽  
The Difference

In this paper, we proposed methods to accurately predict pixel values by effectively using local similarity, curved surface characteristics, and edge characteristics present in an image. Furthermore, to hide more confidential data in a cover image using the prediction image composed of precisely predicted pixel values, we proposed an effective data hiding technique that applied the prediction image to the conventional reversible data hiding technique. Precise prediction of pixel values greatly increases the frequency at the peak point in the histogram of the difference sequence generated using the cover and prediction images. This considerably increases the amount of confidential data that can be hidden in the cover image. The proposed reversible data hiding algorithm (ARDHA) can hide up to 24.5% more confidential data than the existing algorithm. Moreover, it is not possible to determine the presence of hidden confidential data in stego-images, as they possess excellent visual quality. The confidential data can be extracted from the stego-image without loss, and the original cover image can be restored from the stego-image without distortion. Therefore, the proposed algorithm can be effectively used in digital image watermarking, military, and medical applications.

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 Image Steganography Using Pixel Value Differencing (PVD) Technique Based on Firefly Algorithm

2021 ◽  
pp. 80-86
Author(s):  
Oluwaseun M. Alade ◽  
Elizabeth A. Amusan ◽  
Oluyinka T. Adedeji ◽  
Oluwaseun O. Alo
Keyword(s):  
Firefly Algorithm ◽  
Promising Result ◽  
Signal To Noise Ratio ◽  
Text Message ◽  
Image Steganography ◽  
Cover Image ◽  
Experimental Result ◽  
Stego Image ◽  
Pixel Value ◽  
Pixel Value Differencing

Steganography deals with the ways of hiding communicated data in such a way that it remains confidential. Finding best position inside cover image to embed text message, maintaining a reasonable trade-off between security, robustness, higher bit embedding rate and imperceptibility are some of the challenges of steganography system. Hence, this paper presents firefly algorithm for finding best positions inside cover image in order to embed text message into cover image using Pixel Value Differencing (PVD) technique. Four different cover image was used. Experimental result showed the cover image with selected location using firefly algorithm as well as the stego image using PVD technique. The stego image was evaluated using Peak Signal to Noise Ratio (PSNR) and Mean square Error (MSE).  Firefly Algorithm with PVD technique produced a promising result for image steganography.

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 Stego-eHealth: An eHealth System for Secured Transfer of Medical Images using Image Steganography

2021 ◽  
Author(s):  
Nandhini Subramanian ◽  
, Jayakanth Kunhoth ◽  
Somaya Al-Maadeed ◽  
Ahmed Bouridane
Keyword(s):  
Medical Information ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Health Care Systems ◽  
Image Steganography ◽  
Cover Image ◽  
Stego Image ◽  
Hiding Capacity ◽  
Secret Image ◽  
Care Systems

COVID pandemic has necessitated the need for virtual and online health care systems to avoid contacts. The transfer of sensitive medical information including the chest and lung X-ray happens through untrusted channels making it prone to many possible attacks. This paper aims to secure the medical data of the patients using image steganography when transferring through untrusted channels. A deep learning method with three parts is proposed – preprocessing module, embedding network and the extraction network. Features from the cover image and the secret image are extracted by the preprocessing module. The merged features from the preprocessing module are used to output the stego image by the embedding network. The stego image is given as the input to the extraction network to extract the ingrained secret image. Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) are the evaluation metrics used. Higher PSNR value proves the higher security; robustness of the method and the image results show the higher imperceptibility. The hiding capacity of the proposed method is 100% since the cover image and the secret image are of the same size.

scholarly journals Enhancement of medical images using fuzzy logic

2021 ◽  
Vol 23 (3) ◽  
pp. 1478
Author(s):  
Yousra Ahmed Fadil ◽  
Baidaa Al-Bander ◽  
Hussein Y. Radhi
Keyword(s):  
Image Enhancement ◽  
Medical Images ◽  
Signal To Noise Ratio ◽  
Visual Appearance ◽  
Fuzzy C Means Clustering ◽  
Reasonable Limit ◽  
Image Pixels ◽  
The Difference ◽  
Two Stages ◽  
Average Information

Image enhancement is one of the most critical subjects in computer vision and image processing fields. It can be considered as means to enrich the perception of images for human viewers. All kinds of images typically suffer from different problems such as weak contrast and noise. The primary purpose of image enhancement is to change an image's visual appearance. Many algorithms have recently been proposed for enhancing medical images. Image enhancement is still deemed a challenging task. In this paper, the fuzzy c-means clustering (FCM) technique is utilized to enhance the medical images. The method of enhancement consists of two stages. The proposed algorithm conducts a cluster test on the image pixels. It then increases the difference of gray level between the diverse objects to accomplish the enhancement purpose of the medical images. The experimental results have been tested using various images. The algorithm enhanced the small target of the image to a reasonable limit and revealed favorable performance. The results of image enhancement techniques were evaluated by using terms of different criteria such as peak signal to noise ratio (PSNR), mean square error (MSE) and average information contents (AIC), showing promising performance.

scholarly journals A robust way of steganography by using blocks of an image in spatial domain

2019 ◽  
Vol 7 (1) ◽  
pp. 1-7
Author(s):  
Ladeh S. Abdulraman ◽  
Sheerko R. Hma Salah ◽  
Halgurd S. Maghdid ◽  
Azhin T. Sabir
Keyword(s):  
Signal To Noise Ratio ◽  
Text Message ◽  
Circuit Complexity ◽  
Spatial Domain ◽  
Cover Image ◽  
Original Text ◽  
Wide Field ◽  
Secret Data ◽  
Stego Image ◽  
Secret Communication

Steganography is a way to convey secret communication, with rapid electronic communication and high demand of using the internet, steganography has become a wide field of research and discussion. In this paper a new approach for hiding information in cover image proposed in spatial domain, the proposed approach divides the host image into blocks of size (8x8) pixels and message bits are embeds into the pixels of a cover image. The 64-pixel values of each block converted to be represented in binary system and compared with corresponding secret data bits for finding the matching and hold 6-pixels. The search process performed by comparing each secret data bit (8-bits) with created binary plane at the cover image, if matching is found the last row of the created binary plane which is (LSB) is modified to indicate the location of the matched bits sequence “which is the secret data” and number of the row, if matching is not found in all 7th rows the secret sequence is copied in to the corresponding 8th row location.The payload of this technique is 6 pixels’ message (48-bits) in each block. In the experiments secret messages are randomly embedded into different images. The quality of the stego-image from which the original text message is extracted is not affected at all. For validation of the presented mechanism, the capacity, the circuit complexity, and the measurement of distortion against steganalysis is evaluated using the peak-signal-to-noise ratio (PSNR) are analyzed.

scholarly journals Design and Implementation of LSB based Minimum Deviation Steganography technique on High Payload Grayscale Images

2019 ◽  
Vol 9 (2) ◽  
pp. 538-542
Keyword(s):  
Signal To Noise Ratio ◽  
Cover Image ◽  
Hidden Information ◽  
Stego Image ◽  
Successive Block ◽  
Design And Implementation ◽  
Successive Extraction ◽  
Carrier Image ◽  
High Payload ◽  
Grayscale Images

The paper discusses the design of a new steganographic method for 8-bit grayscale images. Here, the input cover image is decomposed into 2 × 2 blocks of pixels which are non-overlapping in row major order. Each block can embed 7- bits from secret bit-stream. Successive block embedding operation ensures the concealment of the entire hidden information into the carrier image. The proposed method offers a fixed payload of 1.75 bits per pixel (bpp) which is considered to be a high payload in the field of Steganography. The degradation of the stego-image is also not severe in our method and that can be analyzed by observing the Peak Signal to Noise Ratio (PSNR) of greater than 30 dB. In the reverse way, the receiver decomposes the cover image into 2 × 2 non-overlapping blocks of pixels in row major order. Successive extraction of 7- secret bits from each block ensures the re-generation of the secret information. Simulation results ensure that the proposed method is superior than other schemes in terms of qualitative clarity of the Stego-image

scholarly journals TEKNIK PENGUJIAN KEAMANAN DATA TEXT BERTINGKAT DENGAN METODE STEGANOGRAPHY LSB DAN TEKNIK ENKRIPSI

2018 ◽  
Vol 8 (2) ◽  
pp. 109-122
Author(s):  
Hillman Akhyar Damanik ◽  
Merry Anggraeni
Keyword(s):  
Mean Square Error ◽  
Signal To Noise Ratio ◽  
Cover Image ◽  
Mean Square ◽  
Least Significant Bit ◽  
Signal To Noise ◽  
Stego Image ◽  
Noise Ratio

Internet adalah media komunikasi paling populer saat ini, tetapi komunikasi melalui internet menghadapi beberapa masalah seperti keamanan data, kontrol hak cipta, kapasitas ukuran data, otentikasi dan lain sebagainya. Pada penelitian ini peneliti memperkenalkan skema untuk menyembunyikan data yang terenkripsi. Dengan menggunakan citra sebagai embedding dan cover image untuk text hiding. Fitur utama skema adalah cara penyematan data teks ke cover image terenkripsi. Peneliti berkonsentrasi menggunakan metode Red-Green-Blue Least Significant Bit (RGB-LSB). Penyematan data teks dan memverifikasi kinerja menggunakan metode RGB-LSB dalam hal indeks kualitas yaitu Peak Signal-to-Noise Ratio (PSNR) dan Mean Square Error (MSE) , imperceptibility dan indeks recovery. Nilai SME pada jumlah pesan yang disisipi sebanyak 407 kata adalah nilai MSE 0.8310 dan nilai PSNR 48.9348. pada jumlah pesan yang disisipi sebanyak 507 kata adalah nilai MSE 0.8322 dan nilai PSNR 48.9285. Nilai kriteria imperceptibility pada stego image menghasilkan image dan nilai-nilai pixel pada masing-masing cover image tidak mengalami perubahan. Aspek recovery pada penyembunyian pesan teks pada masing-masing cover image pada proses embedding, dimensi citra yang berbeda dan sampai proses ekstraksi juga menghasilkan panjang pesan asli terungkap. Berdasarkan hasil perbandingan ini dapat diketahui bahwa algoritma LSB memiliki hasil yang baik pada teknik penyisipan sebuah pesan pada file citra.

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