A Generalized Model of Text Steganography by Summary Generation using Frequency Analysis

Majumder, Anandaprova; Changder, Suvamoy

doi:10.1109/icrito.2018.8748747

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…Ref. [68] suggested a new linguistic text-based steganography technique where the presence of frequently used letter sets or double letter pairs is searched for in the words of the paragraph, where the sentences are in the normalized form. The algorithm identifies the sentences to output its summary, which is also referred to as cover text.…”

Section: Linguisticmentioning

confidence: 99%

A Review on Text Steganography Techniques

et al. 2021

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There has been a persistent requirement for safeguarding documents and the data they contain, either in printed or electronic form. This is because the fabrication and faking of documents is prevalent globally, resulting in significant losses for individuals, societies, and industrial sectors, in addition to national security. Therefore, individuals are concerned about protecting their work and avoiding these unlawful actions. Different techniques, such as steganography, cryptography, and coding, have been deployed to protect valuable information. Steganography is an appropriate method, in which the user is able to conceal a message inside another message (cover media). Most of the research on steganography utilizes cover media, such as videos, images, and sounds. Notably, text steganography is usually not given priority because of the difficulties in identifying redundant bits in a text file. To embed information within a document, its attributes must be changed. These attributes may be non-displayed characters, spaces, resized fonts, or purposeful misspellings scattered throughout the text. However, this would be detectable by an attacker or other third party because of the minor change in the document. To address this issue, it is necessary to change the document in such a manner that the change would not be visible to the eye, but could still be decoded using a computer. In this paper, an overview of existing research in this area is provided. First, we provide basic information about text steganography and its general procedure. Next, three classes of text steganography are explained: statistical and random generation, format-based methodologies, and linguistics. The techniques related to each class are analyzed, and particularly the manner in which a unique strategy is provided for hiding secret data. Furthermore, we review the existing works in the development of approaches and algorithms related to text steganography; this review is not exhaustive, and covers research published from 2016 to 2021. This paper aims to assist fellow researchers by compiling the current methods, challenges, and future directions in this field.

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Section: Linguisticmentioning

confidence: 99%

A Review on Text Steganography Techniques

et al. 2021

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“…Eng. Saad bin Nasser Al Azzam1, Mesopotamian Journal of Cybersecurity Vol.2022,[18][19][20][21][22][23][24][25][26][27] …”

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confidence: 99%

Ubiquitous Trust Management and Power Optimization for UAV Assisted Mobile Communication

2022

MJCS

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The human being sought to find a human variety of techniques to assure data access with complete confidentiality. The transition from the use of. regular text and audio data to digital media has improved data access and transport. It has become relatively simple to intercept data sent across networks or get access to a variety of machines. Steganography is the study of concealing the existence of communication by embedding hidden data in multimedia payloads such as text, image, audio, and video. This project investigates how to improve steganography by merging text and image production to provide invisible encryption, security, and robustness in digital images. Text hide into another text using quality in the proposed system include Mean Square Error (MSE), Normalized Correlation (NC), and Normalized Cross–correlation Mean Squared Error, Histogram Analysis, Standard Deviation, and Statistical Test and Analysis. The algorithm of our suggested system seems to meet the greatest standards of security, perceptions, and capability. Using the standard of ASCII Control characters for a cover word, the procedure for using the processed system is supplied from the cover sentence. The same method is used for other words from different cover sentences, given the line numbers of each cover sentence and Stego sentence.

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