Hiding the Hidden Message: Approaches to Textual Steganography (original) (raw)
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An Approach to Textual Steganography
Textual steganography is a means of concealing an encoded message within text. The appeal in such a system is its potential for hiding the fact that encoding is taking place. The failure to hide the presence of encoding is a form of information leakage and an inherent risk since it suggests that there is important or valuable information in transit. This is considered a major limitation of existing cryptographic techniques as applied to secure information transfer. In this paper, we describe an experimental system that we have developed as a test-bed for textual steganography. This system allows us to explore the application of part of speech tagging, word sense disambiguation and synonym replacement as component strategies for textual steganography.
A Universal Lexical Steganography Technique
International Journal of Computer and Communication Engineering, 2013
A literally meaning of Steganography is "covered writing". There are several methods of steganography, these include: Image steganography, Audio steganography, Video steganography and Linguistic steganography which use the cover to hide information. Each method has its own algorithm to embedding secret information inside the media "cover". Linguistic steganography is basically hiding information in a text in such a way without making the text suspicious, so we have to take into our account possible characteristics of natural languages. In linguistic steganography, digital numbers like (0010100101001) data is to be encoded to innocuous natural language text by using synonym. In this paper, English language will be used as an instance of natural languages as we will be concerned with the set of all natural language texts. this research tries to employ a set of all synonyms as a way to hide secret message inside a natural language text. The main objective of this paper is to develop a general technique of lexical steganography to support different natural languages texts and decrease the bits used for encoding and increase the information. An evaluation of the proposed method has been carried out. The obtained results are encouraging and promising.
Introduction to Linguistic Steganography
Nonlinear Engineering, 2015
The specialty of data covering up has gotten much consideration in the late years as security of data has turn into a major concern in this web time. As sharing of delicate data by means of a typical correspondence station has get to be unavoidable, Steganography – the workmanship and art of concealing data has increased much consideration. We are likewise encompassed by a universe of mystery correspondence, where individuals of numerous types are transmitting data as guiltless as an encoded Visa number to an online store than and as deceptive as a terrorist plot to robbers. Steganography is derived from two Greek words, steganos, meaning covered or secret, and graphia, meaning writing. In simple terms, steganography is the art and science of hiding information in plain sight. Steganography is an innovation where advanced information pressure, data hypothesis, spread range, and cryptography innovations are united to fulfill the requirement for security on the Internet. This paper is...
A New Linguistic Steganography Scheme based on Lexical Substitution
Recent studies in the field of text-steganography shows a promising future for linguistic driven stegosystems. One of the most common techniques in this field is known as lexical substitution which provides the requirements for security and payload capacity. However, the existing lexical substitution schemes need an enormous amount of shared data between sender and receiver which acts as the stego key. In this paper, we propose a novel encoding method to overcome this problem. Our proposed approach preserves the good properties of lexical substitution schemes while it provides short length stego keys and significant robustness against active adversary attacks. We demonstrate high efficiency of the proposed scheme through theoretical and experimental results. Text-steganography; lexical substitution; natural language processing;
Steganography is an ancient art. With the advent of computers, we have vast accessible bodies of data in which to hide information, and increasingly sophisticated techniques with which to analyze and recover that information. While much of the recent research in steganography has been centered on hiding data in images, many of the solutions that work for images are more complicated when applied to natural language text as a cover medium. Many approaches to steganalysis attempt to detect statistical anomalies in cover data which predict the presence of hidden information. Natural language cover texts must not only pass the statistical muster of automatic analysis, but also the minds of human readers. Linguistically naïve approaches to the problem use statistical frequency of letter combinations or random dictionary words to encode information. More sophisticated approaches use context-free grammars to generate syntactically correct cover text which mimics the syntax of natural text. None of these uses meaning as a basis for generation, and little attention is paid to the semantic cohesiveness of a whole text as a data point for statistical attack. This paper provides a basic introduction to steganography and steganalysis, with a particular focus on text steganography. Text-based information hiding techniques are discussed, providing motivation for moving toward linguistic steganography and steganalysis. We highlight some of the problems inherent in text steganography as well as issues with existing solutions, and describe linguistic problems with character-based, lexical, and syntactic approaches. Finally, the paper explores how a semantic and rhetorical generation approach suggests solutions for creating more believable cover texts, presenting some current and future issues in analysis and generation. The paper is intended to be both general enough that linguists without training in information security and computer science can understand the material, and specific enough that the linguistic and computational problems are described in adequate detail to justify the conclusions suggested.
2013
–With the rapid growth of networking mechanisms, where large amount of data can be transferred between users over different media, the necessity of secure systems to maintain data privacy increases significantly. Different techniques have been introduced to encrypt data during the transfer process to avoid any kind of attack. One of these techniques is to hide the data inside another file which is called Steganography. In steganography, data is hidden inside a carrier file where anyone can see, but the hidden data inside it cannot be discovered. To this end, good algorithms can avoid the suspicion of having any attacker by applying some criteria before sending the data. In this paper, we present an algorithm to hide data using a text file as a carrier. Left-Right Remarks that represent Unicode symbols are used to hide the data inside the text file. Moreover, our algorithm can be applied in different size textual data.
Linguistic Grammar Approach to Textual Steganography
Text Steganography is the technique of concealing secret or sensitive data within some text. Sending encrypted data risks drawing attention of hackers and crackers, where they might attempt to crack and reveal the original message. Steganography has gained prominence in the last decade due to the constant need for data concealment. The communicated data or messages can be viewed by an attacker in the network, so work of steganography is to hide these communicated data without giving away the fact that sensitive data is hidden behind them. Various steganography techniques has been proposed in the past, but the problem still remains in hiding text behind some text. The model proposed in this paper reads binary data and uses a dictionary and a style source to generate an innocuous text file that can later be converted back, with the help of the dictionary, to the original data. The dictionary contains valid words, classified according to type.
This paper compares eight proposed methods using steganography of Arabic language texts for different search algorithms to consider a secret key. All methods use random numbers to generate the secret key. The objectives are to evaluate each method and to select the best method that provides the best solution suitable to hide the Arabic language texts. Secret sharing is the fourth-best method in security, linear regression is the best method for transparency and capacity of secret message hiding, whereas singular value decomposition is the best method in terms of security and robustness, Huffman code provides secret message compression security and transparency, and steganography in Microsoft Word documents uses the protocol in layer one of single–double quote, which is weak in security. Conversely, the random subtraction of two images method is the best algorithm in terms of security, robustness, and capacity, while Kashida and Single–double quote are the best methods for security, transparency, and robustness, steganography of twice secret messages in layer one is the best method for security and robustness. Of all the aforementioned security methods, secret sharing is the best overall security method.
Comparison of Eight Proposed Security Methods using Linguistic Steganography Text
International Journal of Computing and Information Sciences, 2016
This paper compares eight proposed methods using steganography of Arabic language texts for different search algorithms to consider a secret key. All methods use random numbers to generate the secret key. The objectives are to evaluate each method and to select the best method that provides the best solution suitable to hide the Arabic language texts. Secret sharing is the fourth-best method in security, linear regression is the best method for transparency and capacity of secret message hiding, whereas singular value decomposition is the best method in terms of security and robustness, Huffman code provides secret message compression security and transparency, and steganography in Microsoft Word documents uses the protocol in layer one of single-double quote, which is weak in security. Conversely, the random subtraction of two images method is the best algorithm in terms of security, robustness, and capacity, while Kashida and Single-double quote are the best methods for security, transparency, and robustness, steganography of twice secret messages in layer one is the best method for security and robustness. Of all the aforementioned security methods, secret sharing is the best overall security method.
A Survey of Text Steganography Methods
International Journal of Scientific Research in Science and Technology, 2021
Phishing is that the most typical and most dangerous attack among cybercrimes. The aim of these attacks is to steal the data that’s utilized by people and organizations to perform transactions or any vital info. The goal of this is often to perform an Extreme Learning Sending encrypted messages frequently will draw the attention of third parties, i.e. hackers, perhaps causing attempts to break and reveal the original messages. In a digital world, steganography is introduced to hide the existence of the communication by concealing a secret message inside another unsuspicious message. This paper presents an overview of text steganography and a brief history of steganography along with various existing text-based steganography techniques.