A reversible modified least significant bit (LSB) matching revisited method

2021 ◽  
pp. 116556
Author(s):  
Hsien-Wen Tseng ◽  
Hui-Shih Leng
Keyword(s):  
Least Significant Bit ◽  
Lsb Matching

scholarly journals Steganography: Securing Message in wireless network

2013 ◽  
Vol 4 (3) ◽  
pp. 797-801 ◽  
Author(s):  
A H M Kamal
Keyword(s):  
Wireless Network ◽  
True Positive Rate ◽  
Modulus Function ◽  
Secret Message ◽  
Least Significant Bit ◽  
Lsb Matching ◽  
Survey Paper ◽  
Binary Space Partition ◽  
Space Partition ◽  
Noise Margin

Steganography is the process of hiding a secret message with in a cover medium. However eavesdropper may guess the embedding algorithm like least significant bit (LSB) replacement of Chan et al, 2004; Wang et al, 2001; Wu et al, 2005, LSB matching of Mielikainen, 2006, addition and/or subtraction of Andead wastfield, 2001; F. Huang et al in 2011, Exploiting Modification Direction by Zhang and Wang, 2006, Binary Space Partition by Tsai and Wang, 2007, modulus function of Chin et al, 2011 and thus can apply the respective extraction method to detect the secret message. So challenges lies in the methodologies of embedding message. Capacity, security and robustness are the services to be demanded by users. Again the true-positive rate of secret message detection by eavesdropper should be lessened by applying firm technique. Thirdly operating domain should be less sensitive to the noise, margin level of losses or alteration of data while communicating through unguided medium like wireless network, sensor network and cellular network. This paper will briefly discuss the steganographic methods and their experimental results explained in the survey paper of Niels Provos and Peter Honeyman to hide and seek message. Finally the proposed results and the directions for future works are addressed.

scholarly journals Improving the Reversible LSB Matching Scheme Based on the Likelihood Re-encoding Strategy

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 577
Author(s):  
Tzu-Chuen Lu ◽  
Ping-Chung Yang ◽  
Biswapati Jana
Keyword(s):  
Image Quality ◽  
Experimental Results ◽  
Least Significant Bit ◽  
Matching Method ◽  
Embedding Method ◽  
Lsb Matching ◽  
Dual Image ◽  
Frequency Occurrence ◽  
Encoding Strategy

In 2018, Tseng et al. proposed a dual-image reversible embedding method based on the modified Least Significant Bit matching (LSB matching) method. This method improved on the dual-image LSB matching method proposed by Lu et al. In Lu et al.’s scheme, there are seven situations that cannot be restored and need to be modified. Furthermore, the scheme uses two pixels to conceal four secret bits. The maximum modification of each pixel, in Lu et al.’s scheme, is two. To decrease the modification, Tseng et al. use one pixel to embed two secret bits and allow the maximum modification to decrease from two to one such that the image quality can be improved. This study enhances Tseng et al.’s method by re-encoding the modified rule table based on the probability of each hiding combination. The scheme analyzes the frequency occurrence of each combination and sets the lowest modified codes to the highest frequency case to significantly reduce the amount of modification. Experimental results show that better image quality is obtained using our method under the same amount of hiding payload.

scholarly journals Indiscernibility Mask Key for Image Steganography

Computers ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 38
Author(s):  
Piotr Artiemjew ◽  
Aleksandra Kislak-Malinowska
Keyword(s):  
Image Steganography ◽  
Least Significant Bit ◽  
Fixed Degree ◽  
Matching Method ◽  
Chi Square ◽  
Lsb Matching ◽  
Experimental Part ◽  
Lsb Technique ◽  
Initial Research

Our concern in this paper is to explore the possibility of using rough inclusions for image steganography. We present our initial research using indiscernibility relation as a steganographic key for hiding information into the stego carrier by means of a fixed mask. The information can be embedded into the stego-carrier in a semi-random way, whereas the reconstruction is performed in a deterministic way. The information shall be placed in selected bytes, which are indiscernible with the mask to a fixed degree. The bits indiscernible with other ratios (smaller or greater) form random gaps that lead to somehow unpredictable hiding of information presence. We assume that in our technique it can modify bits, the change of which does not cause a visual modification detectable by human sight, so we do not limit ourselves to the least significant bit. The only assumption is that we do not use the position when the mask we define uses it. For simplicity’s sake, in this work we present its operation, features, using the Least Significant Bit (LSB) method. In the experimental part, we have implemented our method in the context of hiding image into the image. The LSB technique in its simplest form is not resistant to stegoanalisys, so we used the well-known LSB matching method to mask the presence of our steganographic key usage. To verify the resistance to stegoanalisys we have conducted and discussed Chi-square and LSB enhancement test. The positive features of our method include its simplicity and speed, to decode a message we need to hide, or pass to another channel, a several-bit mask, degree of indiscernibility and size of the hidden file. We hope that our method will find application in the art of creating steganographic keys.

scholarly journals A New Digital Image Steganography Based on Center Embedded Pixel Positioning

2021 ◽  
Vol 21 (2) ◽  
pp. 89-104
Author(s):  
Dedi Darwis ◽  
Akmal Junaidi ◽  
Dewi Asiah Shofiana ◽  
Wamiliana
Keyword(s):  
Digital Image ◽  
Image Steganography ◽  
Cover Image ◽  
Least Significant Bit ◽  
Bottom Part ◽  
New Approach ◽  
Secret Image ◽  
Lsb Matching ◽  
Two Sides ◽  
Sequential Cropping

Abstract In this study we propose a new approach to tackle the cropping problem in steganography which is called Center Embedded Pixel Positioning (CEPP) which is based on Least Significant Bit (LSB) Matching by setting the secret image in the center of the cover image. The evaluation of the experiment indicated that the secret image can be retrieved by a maximum of total 40% sequential cropping on the left, right, up, and bottom of the cover image. The secret image also can be retrieved if the total asymmetric cropping area is 25% that covered two sides (either left-right, left-up or right-up). In addition, the secret image can also be retrieved if the total asymmetric cropping area is 70% if the bottom part is included. If asymmetric cropping area included three sides, then the algorithm fails to retrieve the secret image. For cropping in the botom the secret image can be extracted up to 70%.

scholarly journals Blind Steganalysis for JPEG Images using SVM and SVM-PSO Classifiers

2019 ◽  
Vol 8 (11S) ◽  
pp. 1239-1246 ◽  
Keyword(s):  
Kernel Functions ◽  
Support Vector ◽  
Least Significant Bit ◽  
Jpeg Images ◽  
Lsb Matching ◽  
Universal Steganalysis ◽  
Pixel Value ◽  
Lsb Replacement ◽  
Pixel Value Differencing ◽  
Blind Steganalysis

Blind steganalysis or the universal steganalysis helps to identify hidden information without previous knowledge of the content or the embedding technique. The Support Vector Machine (SVM) and SVM- Particle Swarm Optimization (SVM-PSO) classifiers are adopted for the proposed blind steganalysis. The important features of the JPEG images are extracted using Discrete Cosine Transform (DCT). The kernel functions used for the classifiers in the proposed work are the linear, epanechnikov, multi-quadratic, radial, ANOVA and polynomial. The proposed work uses linear, shuffle, stratified and automatic sampling techniques. The proposed work employs four techniques for image embedding namely, Least Significant Bit (LSB) Matching, LSB replacement, Pixel Value Differencing (PVD) and F5 and applies 25% embedding. The data to the classifier is split as 80:20 for training and testing and 10-fold cross validation is carried out.

STEGANOGRAPHIC METHODS FOR EMBEDDING INFORMATION IN DIGITAL OBJECTS TO PROVIDE INFORMATION SECURITY IN THE CONCEPT OF "INTERNET OF THINGS"

2019 ◽  
pp. 110-116
Author(s):  
Hristo Terziev
Keyword(s):  
Information Security ◽  
Internet Of Things ◽  
Information And Communication Technologies ◽  
Communication Technologies ◽  
Virtual Space ◽  
Least Significant Bit ◽  
Computer Environment ◽  
Information And Communication ◽  
Digital Objects ◽  
Effective Service

Internet of Things is a new world for connecting object space in the real world with virtual space in a computer environment. To build IoT as an effective service platform, end users need to trust the system. With the growing quantity of information and communication technologies, the need to ensure information security and improve data security is increasing. One of the potential solutions for this are steganographic methods. Steganography based on the least significant bit (LSB) is a popular and widely used method in the spatial domain.

STEGANOGRAFI DENGAN MENGGUNAKAN METODE LSB DAN ALGORITMA HILL CIPHER

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Sherly Gina Supratman
Keyword(s):  
Digital Images ◽  
Text Messages ◽  
The Internet ◽  
Digital Imagery ◽  
Least Significant Bit ◽  
Hill Cipher ◽  
Secure Data ◽  
Audio Video ◽  
The Hill

AbstrakJaringan Komunikasi seperti Internet� merupakan jaringan yang tidak aman untuk mentransmisi data, seperti teks, audio,video dan citra digital. Salah satu cara untuk pengamanan data dapat dilakukan dengan menggunakan proses kriptografi dan �steganografi. Penggunaan ini dengan tujuan untuk merahasiakan pesan yang dikirim dan sekaligus menghindarkan pesan tersebut dari kecurigaan pihak lain yang tidak berkepentingan.Pesan yang digunakan dalam makalah ini adalah berupa text dengan menyisipkannya pada gambar. Pada proses kriptografi, pesan yang berupa text akan dienkrip dengan algoritma Hill Chiper, dan kemudian pesan yang telah dienkrip akan dilakukan proses steganografi pada citra digital� 8 bit dengan skala 0 � 255, dengan metode Least Significant Bit ( LSB ).�Kata kunci: Kriptografi, Hill Chiper, Steganografi, Least Significant Bit�AbstractCommunication Networks such as the Internet are unsafe networks for transmitting data, such as text, audio, video and digital imagery. One way to secure data can be done by using cryptography and steganography process. This use is for the purpose of concealing messages being transmitted and avoiding such messages from the suspicion by others who are not interested.The message used in this paper is text by inserting it in the image. In the cryptographic process, text messages will be encrypted with the Hill Chiper algorithm, and then the encrypted message will be steganographed on 8-bit digital images on a scale of 0-255, using the Least Significant Bit (LSB) method.�Keywords: Cryptography, Hill Chiper, Steganography, Least Significant Bit

KOMBINASI KRIPTOGRAFI RC4 DAN STEGANOGRAFI LSB PADA CITRA DIGITAL DENGAN FORMAT BITMAP UNTUK MENJAGA KEAMANAN PESAN

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Ellya Helmud
Keyword(s):  
Least Significant Bit

ABSTRAK Keamanan dan kerahasiaan suatu pesan merupakan hal yang harus dijaga. Kebutuhan untuk menjaga keamanan pesan dan menjaga kerahasiaan pesan dibutuhkan dua metode yang berbeda, dimana untuk menjaga keamanan pesan digunakan kriptografi dan untuk menjaga kerahasiaan pesan digunakan steganografi. Pada penelitian ini, penulis mengkombinasikan kriptografi dan steganografi untuk menjaga keamanan dan kerahasiaan pesan. Kriptografi yang digunakan menggunakan algoritma RC4 dan steganografi yang digunakan menggunakan metode Least Significant Bit (LSB). Pada penelitian ini pengujian dilakukan dengan perangkat lunak Visual Studio 2008 dan untuk hasil gambar yang dihasilkan diuji menggunakan Matlab R2015b. Pengujian waktu pada proses enkripsi dan dekripsi menggunakan algoritma RC4 dilakukan sebanyak 10 kali dari jumlah karakter 100 hingga 1000 karakter, kemudian gambar yang dihasilkan mempunyai nilai error dan nilai kualitas yang tidak jauh berbeda. Kata Kunci: Kriptografi, Steganografi, LSB, RC4

A multi-octave microwave 6-bit true time delay with low amplitude and delay variation in 65 nm CMOS

2021 ◽  
pp. 1-10
Author(s):  
Yakov Gutkin ◽  
Asher Madjar ◽  
Emanuel Cohen
Keyword(s):  
Time Delay ◽  
Insertion Loss ◽  
Impedance Matching ◽  
Least Significant Bit ◽  
Delay Cell ◽  
True Time Delay ◽  
Unit Cells ◽  
True Time ◽  
And Performance ◽  
Low Amplitude

Abstract In this paper, we describe the design, layout, and performance of a 6-bit TTD (true time delay) chip operating over the entire band of 2–18 GHz. The 1.15 mm2 chip is implemented using TSMC foundry 65 nm technology. The least significant bit is 1 ps. The design is based on the concept of all-pass network with some modifications intended to reduce the number of unit cells. Thus, the first three bits are implemented in a single delay cell. A peaking buffer amplifier between bit 4 and bit 5 is used for impedance matching and partial compensation of the insertion loss slope. The rms delay error of the TTD is <1 ps over most of the frequency band and insertion loss is between 2.5 and 6.3 dB for all 64 states.

scholarly journals Robust Secret Image Sharing Resistant to Noise in Shares

2021 ◽  
Vol 17 (1) ◽  
pp. 1-22
Author(s):  
Xuehu Yan ◽  
Lintao Liu ◽  
Longlong Li ◽  
Yuliang Lu
Keyword(s):  
Chinese Remainder Theorem ◽  
Recovery Phase ◽  
Error Correcting Codes ◽  
Secret Image Sharing ◽  
Data Loss ◽  
Least Significant Bit ◽  
Recovery Method ◽  
Secret Image ◽  
Image Sharing ◽  
Salt And Pepper

A secret image is split into   shares in the generation phase of secret image sharing (SIS) for a  threshold. In the recovery phase, the secret image is recovered when any   or more shares are collected, and each collected share is generally assumed to be lossless in conventional SIS during storage and transmission. However, noise will arise during real-world storage and transmission; thus, shares will experience data loss, which will also lead to data loss in the secret image being recovered. Secret image recovery in the case of lossy shares is an important issue that must be addressed in practice, which is the overall subject of this article. An SIS scheme that can recover the secret image from lossy shares is proposed in this article. First, robust SIS and its definition are introduced. Next, a robust SIS scheme for a  threshold without pixel expansion is proposed based on the Chinese remainder theorem (CRT) and error-correcting codes (ECC). By screening the random numbers, the share generation phase of the proposed robust SIS is designed to implement the error correction capability without increasing the share size. Particularly in the case of collecting noisy shares, our recovery method is to some degree robust to some noise types, such as least significant bit (LSB) noise, JPEG compression, and salt-and-pepper noise. A theoretical proof is presented, and experimental results are examined to evaluate the effectiveness of our proposed method.

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