scholarly journals Keamanan Pesan Rahasia Menggunakan Steganografi DCT (Discrete Cosine Transform) pada Citra JPEG

2019 ◽  
Vol 9 (2) ◽  
Author(s):  
Dian Hafidh Zulfikar
Keyword(s):  
Discrete Cosine Transform ◽  
Spatial Domain ◽  
Cover Image ◽  
Secret Message ◽  
Least Significant Bit ◽  
Cosine Transform ◽  
Secret Information ◽  
Dct Coefficients ◽  
Lsb Technique ◽  
Dct Coefficient

<p class="SammaryHeader" align="center"><strong><em>Abstract</em></strong><em></em></p><p><em> </em>The  least significant-bit (LSB) based techniques are very popular for steganography in spatial domain. The simplest LSB technique simply replaces the LSB in the cover image with the  bits from secret information. Further advanced techniques use some criteria to identify the pixels in which LSB(s) can be replaced with the bits of secret information. In Discrete Cosine Transform (DCT) based technique insertion of secret information in carrier depends on the DCT coefficients. Any DCT coefficient value above proper threshold is a potential place for insertion of secret information.</p><p class="Abstrak"><strong> </strong><strong>Keywords :</strong> Discrete Cosine Transform (DCT), steganography, secret message</p><p><strong><em> </em><em>Abstra</em><em>k</em></strong></p><p>Pada steganografi domain spasial, teknik least significant-bit (LSB) merupakan teknik yang paling banyak digunakan pada steganografi. Teknik yang sederhana yang hanya mengubah nilai LSB pada cover image dengan nilai bit pesan rahasia, atau dengan teknik yang lebih baik lagi yaitu dengan menentukan bit-bit LSB mana yang akan dilakukan pergantian nilai bit. Lain halnya dengan metode Discrete Cosine Transform (DCT), teknik steganografi ini akan menyembunyikan informasi rahasia tergantung dari nilai Koefisien DCT.</p><p class="Abstrak"> </p><p class="Abstrak"><strong>Kata Kunci :</strong> Steganografi, DCT, Citra, JPEG, Pesan Rahasia</p>

scholarly journals Optimal Image Steganography Content Destruction Techniques

2021 ◽  
Vol 15 ◽  
pp. 84-88
Author(s):  
Siddeeq Y. Ameen ◽  
Muthana R. Al-Badrany
Keyword(s):  
Discrete Cosine Transform ◽  
Image Steganography ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Least Significant Bit ◽  
Hidden Information ◽  
Random Data ◽  
Cosine Transform ◽  
Wavelet Techniques ◽  
Lsb Technique

The paper presents two approaches for destroying steganogrphy content in an image. The first is the overwriting approach where a random data can be written again over steganographic images whereas the second approach is the denoising approach. With the second approach two kinds of destruction techniques have been adopted these are filtering and discrete wavelet techniques. These two approaches have been simulated and evaluated over two types of hiding techniques, Least Significant Bit LSB technique and Discrete Cosine Transform DCT technique. The results of the simulation show the capability of both approaches to destroy the hidden information without any alteration to the cover image except the denoising approach enhance the PSNR in any received image even without hidden information by an average of 4dB.

scholarly journals Steganalysis of Stegostorage Library

2016 ◽  
Vol 67 (1) ◽  
pp. 99-116
Author(s):  
Michala Gulášová ◽  
Matúš Jókay
Keyword(s):  
Secret Message ◽  
Hamming Code ◽  
Least Significant Bit ◽  
Hamming Codes ◽  
Dct Coefficients ◽  
Random Embeddings ◽  
Dct Coefficient

Abstract The main goal of this research is the detection of the secret messages hidden in JPEG files, which were embedded by StegoStorage library. This tool allows the user to embed any type of information into a folder of images. Sequential, pseudo-random or Hamming code-based embedding into the least significant bit (LSB) of DCT coefficients is possible. It is possible to choose what fraction of capacity of the cover files are filled. The aim of this contribution is to test the statistical LSB embedding model (modified weighted-stego analysis) for all modes of embedding which StegoStorage library offers, and for all cover files’ capacities, respectively. Another goal is to implement a more appropriate type of steganalytic attack for Hamming codes and test it. For this purpose, the RS (Regular/Singular) steganalysis was selected. The detectability of the LSB embedding model of sequential embedding is possible if the cover files are filled to at least one percent of capacity. In the case of pseudo-random embedding, the secret message can be detected if the cover files are filled to at least 10% of their capacity. Hamming codes were undetectable using this type of an attack. In the case of attack by RS steganalysis, another situation arose. When sequential or pseudo-random embeddings were used, the results indicated the detectability was possible if the cover files were filled up at least 5 percent of capacity. The capacity filling of 5 percent corresponds to 2.5 percent of DCT coefficient changes from the original media in the case of sequential embedding. This value, 2.5%, is the threshold for the utilization of Hamming codes, too. Therefore, Hamming codes (7, 4), (15, 11) and (32, 26) indicated the detectability, because they exceeded that limit.

POPULAR DCT MODELS

2007 ◽  
Vol 05 (05) ◽  
pp. 725-733 ◽  
Author(s):  
SARALEES NADARAJAH ◽  
SAMUEL KOTZ
Keyword(s):  
Discrete Cosine Transform ◽  
Bayesian Approach ◽  
Laplace Distribution ◽  
Natural Images ◽  
Superior Performance ◽  
Cosine Transform ◽  
Dct Coefficients ◽  
Dct Coefficient

It is well known that the distribution of the discrete cosine transform (DCT) coefficients of most natural images follows a Laplace distribution. In this note, using a Bayesian approach, we derive two popular models for the distribution of the actual DCT coefficient. We illustrate the superior performance of these models over the standard Laplace model.

scholarly journals A Modulo Function-Based Robust Asymmetric Variable Data Hiding Using DCT

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1659
Author(s):  
Sahib Khan ◽  
Khalil Khan ◽  
Arslan Arif ◽  
Mahmoud Hassaballah ◽  
Jehad Ali ◽  
...  
Keyword(s):  
Data Hiding ◽  
Low Frequency ◽  
Variable Number ◽  
Cover Image ◽  
Secret Message ◽  
Secret Information ◽  
High Data ◽  
Asymmetric Data ◽  
Dct Coefficients ◽  
Variable Data

This work presents a new asymmetric data hiding technique that hides a variable number of secret message bits in the discrete cosine transform (DCT) coefficients of a cover image using a modular distance technique. Prior to data hiding, the proposed framework transforms a cover image from a spatial domain to various frequency coefficients using DCT. The DCT coefficients are arranged in two groups: one with low-frequency coefficient, and the other with the medium and high-frequency coefficients. The medium and higher frequency coefficients are processed for variable data hiding asymmetrically. The proposed technique hides variable sets of secret information bits in different coefficients. The variation in hidden secret information is maintained using a key developed based on the modulo of distance of a coefficient from the reference point. The same key is also used to retrieve the confidential information at the receiver ends. The results reveal that the presented framework does not create any visually significant distortion, and thus the hidden information does not attract the human visual system (HVS). The technique also results in high data hiding efficiency.

scholarly journals A combination of least significant bit and deflate compression for image steganography

2022 ◽  
Vol 12 (1) ◽  
pp. 358
Author(s):  
Huda Kadhim Tayyeh ◽  
Ahmed Sabah Ahmed AL-Jumaili
Keyword(s):  
Data Compression ◽  
State Of The Art ◽  
Image Steganography ◽  
Cover Image ◽  
Huffman Coding ◽  
Secret Message ◽  
Least Significant Bit ◽  
Stable Performance ◽  
Image Pixels ◽  
Lsb Technique

Steganography is one of the cryptography techniques where secret information can be hidden through multimedia files such as images and videos. Steganography can offer a way of exchanging secret and encrypted information in an untypical mechanism where communicating parties can only interpret the secret message. The literature has shown a great interest in the least significant bit (LSB) technique which aims at embedding the secret message bits into the most insignificant bits of the image pixels. Although LSB showed a stable performance of image steganography yet, many works should be done on the message part. This paper aims to propose a combination of LSB and Deflate compression algorithm for image steganography. The proposed Deflate algorithm utilized both LZ77 and Huffman coding. After compressing the message text, LSB has been applied to embed the text within the cover image. Using benchmark images, the proposed method demonstrated an outperformance over the state of the art. This can proof the efficacy of using Deflate as a data compression prior to the LSB embedding.

scholarly journals The use of Least Significant Bit (LSB) and Knight Tour Algorithm for image steganography of cover image

2019 ◽  
Vol 9 (6) ◽  
pp. 5218
Author(s):  
Soo Ann Nie ◽  
Ghazali Sulong ◽  
Rozniza Ali ◽  
Andrew Abel
Keyword(s):  
Cover Image ◽  
Secret Message ◽  
Discrete Wavelet ◽  
Receiver Side ◽  
Test Image ◽  
Least Significant Bit ◽  
Stego Image ◽  
Chi Square ◽  
The Common ◽  
Lsb Technique

<span lang="EN-US">Steganography is one of the method to communicate in a hidden way. In another word, steganography literally means the practice of hiding messages or information within another data. Previous studies have proposed various steganography techniques using different approaches including Least Significant Bit (LSB), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). However, different approaches still have its own weaknesses. Therefore image stenography using Knight Tour Algorithm with Least Significant Bit (LSB) technique is presented. The main objective is to improve the security factor in the stego image. Basically, the proposed technique is divided into two parts which are the sender and receiver side. Then, steganalysis which is a type of attack on stenography algorithm is used to detect the secret message in the cover image by the statistical analysis of pixel values. Chi Square Statistical Attach which is one of the type of steganalysis is used to detect these near-equal Po Vs in images and bases the probability of embedding on how close to equal the even pixel values and their corresponding odd pixel values are in the test image. The Knight Tour Algorithm is applied due to the common Least Significant Bit technique that is weak in security and easily decoded by outsider.</span>

LWT-DCT based Image Watermarking Scheme using Normalized SVD

2020 ◽  
Vol 13 ◽  
Author(s):  
Rahul Dixit ◽  
Amita Nandal ◽  
Arvind Dhaka ◽  
Vardan Agarwal ◽  
Yohan Varghese
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Discrete Cosine Transform ◽  
Image Watermarking ◽  
Singular Value ◽  
Cover Image ◽  
Lifting Wavelet Transform ◽  
Cosine Transform ◽  
Lifting Wavelet ◽  
Value Decomposition

Background: Nowadays information security is one of the biggest issues of social networks. The multimedia data can be tampered with, and the attackers can then claim its ownership. Image watermarking is a technique that is used for copyright protection and authentication of multimedia. Objective: We aim to create a new and more robust image watermarking technique to prevent illegal copying, editing and distribution of media. Method : The watermarking technique proposed in this paper is non-blind and employs Lifting Wavelet Transform on the cover image to decompose the image into four coefficient matrices. Then Discrete Cosine Transform is applied which separates a selected coefficient matrix into different frequencies and later Singular Value Decomposition is applied. Singular Value Decomposition is also applied to the watermarking image and it is added to the singular matrix of the cover image which is then normalized followed by the inverse Singular Value Decomposition, inverse Discrete Cosine Transform and inverse Lifting Wavelet Transform respectively to obtain an embedded image. Normalization is proposed as an alternative to the traditional scaling factor. Results: Our technique is tested against attacks like rotation, resizing, cropping, noise addition and filtering. The performance comparison is evaluated based on Peak Signal to Noise Ratio, Structural Similarity Index Measure, and Normalized Cross-Correlation. Conclusion: The experimental results prove that the proposed method performs better than other state-of-the-art techniques and can be used to protect multimedia ownership.

Eliminating illumination effects by discrete cosine transform (DCT) coefficients' attenuation and accentuation

2013 ◽  
Author(s):  
Shan Du ◽  
Mohamed Shehata ◽  
Wael Badawy ◽  
Choudhury A. Rahman
Keyword(s):  
Discrete Cosine Transform ◽  
Cosine Transform ◽  
Dct Coefficients

A Novel Hybrid Discrete Cosine Transform Speeded Up Robust Feature-Based Secure Medical Image Watermarking Algorithm

2020 ◽  
Vol 10 (11) ◽  
pp. 2588-2599
Author(s):  
Saqib Ali Nawaz ◽  
Jingbing Li ◽  
Uzair Aslam Bhatti ◽  
Anum Mehmood ◽  
Raza Ahmed ◽  
...  
Keyword(s):  
Discrete Cosine Transform ◽  
Digital Watermarking ◽  
Copyright Protection ◽  
Image Watermarking ◽  
Image Feature ◽  
Feature Descriptor ◽  
Cosine Transform ◽  
Speeded Up Robust Features ◽  
Feature Based ◽  
Dct Coefficients

With the advancement of networks and multimedia, digital watermarking technology has received worldwide attention as an effective method of copyright protection. Improving the anti-geometric attack ability of digital watermarking algorithms using image feature-based algorithms have received extensive attention. This paper proposes a novel robust watermarking algorithm based on SURF-DCT perceptual hashing (Speeded Up Robust Features and Discrete Cosine Transform), namely blind watermarking. We design and implement a meaningful binary watermark embedding and extraction algorithm based on the SURF feature descriptor and discrete-cosine transform domain digital image watermarking algorithm. The algorithm firstly uses the affine transformation with a feature matrix and chaotic encryption technology to preprocess the watermark image, enhance the confidentiality of the watermark, and perform block and DCT coefficients extraction on the carrier image, and then uses the positive and negative quantization rules to modify the DCT coefficients. The embedding of the watermark is completed, and the blind extraction of the watermark realized. Correlation values are more than 90% in most of the attacks. It provides better results against different noise attacks and also better performance against rotation. Transparency and high computational efficiency, coupled with dual functions of copyright protection and content authentication, is the advantage of the proposed algorithm.

scholarly journals High-Capacity Image Steganography Algorithm Based on Image Style Transfer

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xinliang Bi ◽  
Xiaoyuan Yang ◽  
Chao Wang ◽  
Jia Liu
Keyword(s):  
High Capacity ◽  
Image Features ◽  
Image Steganography ◽  
Cover Image ◽  
Secret Message ◽  
The Internet ◽  
Stego Image ◽  
Style Transfer ◽  
Secret Image ◽  
Secret Information

Steganography is a technique for publicly transmitting secret information through a cover. Most of the existing steganography algorithms are based on modifying the cover image, generating a stego image that is very similar to the cover image but has different pixel values, or establishing a mapping relationship between the stego image and the secret message. Attackers will discover the existence of secret communications from these modifications or differences. In order to solve this problem, we propose a steganography algorithm ISTNet based on image style transfer, which can convert a cover image into another stego image with a completely different style. We have improved the decoder so that the secret image features can be fused with style features in a variety of sizes to improve the accuracy of secret image extraction. The algorithm has the functions of image steganography and image style transfer at the same time, and the images it generates are both stego images and stylized images. Attackers will pay more attention to the style transfer side of the algorithm, but it is difficult to find the steganography side. Experiments show that our algorithm effectively increases the steganography capacity from 0.06 bpp to 8 bpp, and the generated stylized images are not significantly different from the stylized images on the Internet.

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