scholarly journals Combining Invisible Unicode Characters To Hide Information In A Text Document

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
N.R. Zaynalov ◽  
U.Kh. Narzullaev ◽  
A.N. Muhamadiev ◽  
I.R. Rahmatullaev ◽  
R.K. Buranov
Keyword(s):  
Human Perception ◽  
Secret Message ◽  
Text Documents ◽  
Additional Information ◽  
Chemical Reagents ◽  
Text Document ◽  
Hide Information ◽  
Perception System ◽  
Digital Objects ◽  
Audio Video

Steganography develops tools and methods for hiding the fact of message transmission. The first traces of steganographic methods are lost in ancient times. For example, there is a known method of hiding a written message: the slave's head was shaved, a message was written on the scalp, and after the hair grew back, the slave was sent to the addressee. From detective works, various methods of secret writing between the lines of ordinary text are well known: from milk to complex chemical reagents with subsequent processing. Digital steganography is based on hiding or embedding additional information in digital objects while causing some distortion of these objects. In this case, text, images, audio, video, network packets, and so on can be used as objects or containers. To embed a secret message, steganographic methods rely on redundant container information or properties that the human perception system cannot distinguish. Recently, there has been a lot of research in the field of hiding information in a text container, since many organizations widely use text documents. Based on this, here the MS Word document is considered as a medium of information. MS Word documents have different parameters, and by changing these parameters or properties, you can achieve data embedding. In the same article, we present steganography using invisible Unicode characters of the Space type, but with a different encoding.

scholarly journals Features of using Invisible Signs in the Word Environment for Hiding Data

2019 ◽  
Vol 8 (9S3) ◽  
pp. 1377-1379
Keyword(s):  
Human Perception ◽  
Word Processor ◽  
Redundant Information ◽  
Storage Medium ◽  
Text Documents ◽  
Additional Information ◽  
Text Document ◽  
Perception System ◽  
Digital Objects ◽  
Audio Video

Considered digital steganography is the direction of classical steganography based on concealing or introducing additional information into digital objects, while causing some distortions of these objects. At the same time, images, audio, video, network packets, etc. can be used as objects or containers. Recently, there has been a lot of publication in the field of information hiding in a text container. To embed a secret, steganographic methods rely on redundant information about the used covering media or properties that the human perception system cannot distinguish. Since text documents are widely used in organizations, using a text document as a storage medium may be the preferred choice in such an environment. On the other hand, the choice of using a text document as a storage medium is the most difficult, since it contains less redundant information. In this article, we present textual steganography using invisible characters in a word processor.

scholarly journals Image steganography based on DNA sequence translation properties

2020 ◽  
Vol 4 (6) ◽  
pp. 15-26
Author(s):  
Abdullah Abdullah ◽  
Sardar Ali ◽  
Ramadhan Mstafa ◽  
Vaman Haji
Keyword(s):  
Information Security ◽  
Dna Sequence ◽  
Secure Communication ◽  
Secret Message ◽  
Least Significant Bit ◽  
Sensitive Data ◽  
Translation Process ◽  
Hide Information ◽  
Authorized Access ◽  
Audio Video

Digital communication has become a vital part of daily life nowadays, many applications are using internet-based communication and here the importance of security rose to have a secure communication between two parties to prevent authorized access to sensitive data. These requirements led to a number of research in information security that has been done in the past two decades. Cryptography and steganography are the two main methods that are being used for information security. Cryptography refers to techniques that encrypt a message to be sent to a destination using different methods to be done. On the other hand, steganography is the science of hiding information from others using another cover message or media such as image, audio, video, and DNA sequence. This paper proposed a new method to hide information in an image using the least significant bit (LSB) based on Deoxyribonucleic Acid (DNA) sequence. To accomplish this, the proposed scheme used properties of DNA sequence when codons that consist of three nucleotides are translated to proteins. The LSB of two pixels from the image are taken to represent a codon and then translate them to protein. The secret message bits are injected into codons before the translation process which slightly distorts the image and makes the image less suspicious and hard to detect the hidden message. The experimental results indicate the effeteness of the proposed method.

scholarly journals Image steganography based on DNA sequence translation properties

2020 ◽  
Vol 4 (6) ◽  
pp. 15-26
Author(s):  
Abdullah Ahmed Abdullah ◽  
Sardar Hasen Ali ◽  
Ramadhan J. Mstafa ◽  
Vaman Mohammed Haji
Keyword(s):  
Information Security ◽  
Dna Sequence ◽  
Secure Communication ◽  
Secret Message ◽  
Least Significant Bit ◽  
Sensitive Data ◽  
Translation Process ◽  
Hide Information ◽  
Authorized Access ◽  
Audio Video

Digital communication has become a vital part of daily life nowadays, many applications are using internet-based communication and here the importance of security rose to have a secure communication between two parties to prevent authorized access to sensitive data. These requirements led to a number of research in information security that has been done in the past two decades. Cryptography and steganography are the two main methods that are being used for information security. Cryptography refers to techniques that encrypt a message to be sent to a destination using different methods to be done. On the other hand, steganography is the science of hiding information from others using another cover message or media such as image, audio, video, and DNA sequence. This paper proposed a new method to hide information in an image using the least significant bit (LSB) based on Deoxyribonucleic Acid (DNA) sequence. To accomplish this, the proposed scheme used properties of DNA sequence when codons that consist of three nucleotides are translated to proteins. The LSB of two pixels from the image are taken to represent a codon and then translate them to protein. The secret message bits are injected into codons before the translation process which slightly distorts the image and makes the image less suspicious and hard to detect the hidden message. The experimental results indicate the effeteness of the proposed method.

An Improved B-hill Climbing Optimization Technique for Solving the Text Documents Clustering Problem

2020 ◽  
Vol 16 (4) ◽  
pp. 296-306 ◽  
Author(s):  
Laith Mohammad Abualigah ◽  
Essam Said Hanandeh ◽  
Ahamad Tajudin Khader ◽  
Mohammed Abdallh Otair ◽  
Shishir Kumar Shandilya
Keyword(s):  
Optimization Technique ◽  
Document Clustering ◽  
Text Clustering ◽  
Hill Climbing ◽  
Text Documents ◽  
Clustering Problem ◽  
Text Document ◽  
Text Information ◽  
Amount Of Knowledge ◽  
The Hill

Background: Considering the increasing volume of text document information on Internet pages, dealing with such a tremendous amount of knowledge becomes totally complex due to its large size. Text clustering is a common optimization problem used to manage a large amount of text information into a subset of comparable and coherent clusters. Aims: This paper presents a novel local clustering technique, namely, β-hill climbing, to solve the problem of the text document clustering through modeling the β-hill climbing technique for partitioning the similar documents into the same cluster. Methods: The β parameter is the primary innovation in β-hill climbing technique. It has been introduced in order to perform a balance between local and global search. Local search methods are successfully applied to solve the problem of the text document clustering such as; k-medoid and kmean techniques. Results: Experiments were conducted on eight benchmark standard text datasets with different characteristics taken from the Laboratory of Computational Intelligence (LABIC). The results proved that the proposed β-hill climbing achieved better results in comparison with the original hill climbing technique in solving the text clustering problem. Conclusion: The performance of the text clustering is useful by adding the β operator to the hill climbing.

scholarly journals Distributed data hiding in multi-cloud storage environment

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Leonel Moyou Metcheka ◽  
René Ndoundam
Keyword(s):  
Cloud Storage ◽  
Network Protocols ◽  
Secret Message ◽  
Covert Channel ◽  
Distributed Data ◽  
Comparison Results ◽  
Major Interest ◽  
Cloud Storage Environment ◽  
Audio Video ◽  
Multi Cloud

AbstractClassical or traditional steganography aims at hiding a secret in cover media such as text, image, audio, video or even in network protocols. Recent research has improved this approach called distributed steganography by fragmenting the secret message and embedding each secret piece into a distinct cover media. The major interest of this approach is to make the secret message detection extremely difficult. However, these file modifications leave fingerprints which can reveal a secret channel to an attacker. Our contribution is a new steganography paradigm transparent to any attacker and resistant to the detection and the secret extraction. Two properties contribute to achieve these goals: the files do not undergo any modification while the distribution of the secret in the multi-cloud storage environment allows us to hide the existence of the covert channel between the communicating parties. Information’s are usually hidden inside the cover media. In this work, the covert media is a pointer to information. Therefore the file carries the information without being modified and the only way to access it is to have the key. Experiments show interesting comparison results with remarkable security contributions. The work can be seen as a new open direction for further research in the field.

scholarly journals Development of the documents comparison module for an electronic document management system

2019 ◽  
pp. 527-533
Author(s):  
M A Mikheev ◽  
P Y Yakimov
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Document Management ◽  
Electronic Document ◽  
Text Documents ◽  
Text Document ◽  
Document Management System ◽  
Optical Character ◽  
Electronic Document Management ◽  
Scanned Image

The article is devoted to solving the problem of document versions comparison in electronic document management systems. Systems-analogues were considered, the process of comparing text documents was studied. In order to recognize the text on the scanned image, the technology of optical character recognition and its implementation — Tesseract library were chosen. The Myers algorithm is applied to compare received texts. The software implementation of the text document comparison module was implemented using the solutions described above.

scholarly journals The Evaluation of Accuracy Performance in an Enhanced Embedded Feature Selection for Unstructured Text Classification

2020 ◽  
pp. 3397-3407
Author(s):  
Nur Syafiqah Mohd Nafis ◽  
Suryanti Awang
Keyword(s):  
Feature Selection ◽  
Text Classification ◽  
Training Dataset ◽  
Recursive Feature Elimination ◽  
High Dimensional ◽  
Significant Feature ◽  
Support Vector ◽  
Svm Classifier ◽  
Text Documents ◽  
Text Document

Text documents are unstructured and high dimensional. Effective feature selection is required to select the most important and significant feature from the sparse feature space. Thus, this paper proposed an embedded feature selection technique based on Term Frequency-Inverse Document Frequency (TF-IDF) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) for unstructured and high dimensional text classificationhis technique has the ability to measure the feature’s importance in a high-dimensional text document. In addition, it aims to increase the efficiency of the feature selection. Hence, obtaining a promising text classification accuracy. TF-IDF act as a filter approach which measures features importance of the text documents at the first stage. SVM-RFE utilized a backward feature elimination scheme to recursively remove insignificant features from the filtered feature subsets at the second stage. This research executes sets of experiments using a text document retrieved from a benchmark repository comprising a collection of Twitter posts. Pre-processing processes are applied to extract relevant features. After that, the pre-processed features are divided into training and testing datasets. Next, feature selection is implemented on the training dataset by calculating the TF-IDF score for each feature. SVM-RFE is applied for feature ranking as the next feature selection step. Only top-rank features will be selected for text classification using the SVM classifier. Based on the experiments, it shows that the proposed technique able to achieve 98% accuracy that outperformed other existing techniques. In conclusion, the proposed technique able to select the significant features in the unstructured and high dimensional text document.

Assessment of Twitter Data Clusters with Cosine-Based Validation Metrics Using Hybrid Topic Models

2020 ◽  
Vol 25 (6) ◽  
pp. 755-769
Author(s):  
Noorullah R. Mohammed ◽  
Moulana Mohammed
Keyword(s):  
Data Clustering ◽  
Topic Models ◽  
Cluster Validity ◽  
Text Documents ◽  
Text Data ◽  
Validity Assessment ◽  
Text Document ◽  
Cluster Validity Indices ◽  
Validity Indices ◽  
Data Clusters

Text data clustering is performed for organizing the set of text documents into the desired number of coherent and meaningful sub-clusters. Modeling the text documents in terms of topics derivations is a vital task in text data clustering. Each tweet is considered as a text document, and various topic models perform modeling of tweets. In existing topic models, the clustering tendency of tweets is assessed initially based on Euclidean dissimilarity features. Cosine metric is more suitable for more informative assessment, especially of text clustering. Thus, this paper develops a novel cosine based external and interval validity assessment of cluster tendency for improving the computational efficiency of tweets data clustering. In the experimental, tweets data clustering results are evaluated using cluster validity indices measures. Experimentally proved that cosine based internal and external validity metrics outperforms the other using benchmarked and Twitter-based datasets.

QUANTUM SECURE DIRECT COMMUNICATION WITH QUANTUM IDENTIFICATION

2012 ◽  
Vol 10 (01) ◽  
pp. 1250008 ◽  
Author(s):  
ZHI-WEI SUN ◽  
RUI-GANG DU ◽  
DONG-YANG LONG
Keyword(s):  
High Efficiency ◽  
Quantum Secure Direct Communication ◽  
Secret Message ◽  
Noisy Environments ◽  
Cluster States ◽  
Direct Communication ◽  
Additional Information ◽  
Two Photon ◽  
Transmission Of Information ◽  
Quantum Identification

A one-way quantum secure direct communication protocol with quantum identification utilizing two-photon three-qubit linear cluster states is proposed. The protocol can be used to transmit a secret message and identify user's identification simultaneously. The transmission of information is instantaneous, i.e. the information can be decoded during the transmission and no final transmission of additional information is needed. We prove its robustness against attacks: Any attempt of an adversary to obtain information (and even a bit of information) necessarily induces some errors that the legitimate parties could notice, even in noisy environments. Moreover, this protocol achieves a high efficiency and source capacity since more qubits can be encoded on the same photon.

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