Jun 16, 2012

Normal Linguistic Steganography Methodology: Covert Communications and the Noiseless Steganography Paradigm

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Normal Linguistic Steganography Cover

Normal Linguistic Steganography Methodology:

Covert Communications and the Noiseless Steganography Paradigm 



Ty dåedfo syd tedia umladessy stekanografissy itam dwr Valso Åakseg Eikkjefobryd (VÅE) evbyst ad evjyst. Kjeilogre, avkka tilideikk deid avver tarseg radeindne. Ty tilhyg syd umladessy stekanografissy itam ad an neksom kjevetilbryd myf nysg omfor ny deogs evjst an nekjeat ny deogs gengfordwn. Evjyst mætire syd remaaws stekanografissy ny deellf einolfor nytesu nomk handrese dwy kjekoso dvav, umidso, myrtkassy dwr tilnygesom:


Linguistic steganography is the scientic art of avoiding the conception of suspicion in covert communications by concealing data in a linguistic based textual cover. The goal is not to hinder the adversary from decoding the hidden message, but to prevent the arousal of suspicion in covert communications. Fundamentally, when using any steganographic technique if suspicion is raised, the goal of steganography is defeated regardless of whether or not a plaintext is revealed.


Hanedhan ad oalva aaltide myre eltatdyr NORMALS VÅE iandd, dwr ilju rart keert hevkaum mø hanadstssy VÅE dwy hanesog ny dysat derivvi fy my ty kjeanvarbryd tydkbryd. Iidva, hanedhan ad oalva aaltide myre vartihedyr am njehadyr tydi NORMALS VÅE kakfo mø remaaaws VÅE ad hevkehande. Egt hanesog vald mø vardtforaws ilnese sjeensu idstu NORMALS VÅE ad hanenn emame dwy mø nysge stekanografissy itamfy.


Stidein hanedhan ad oalva aaltide myre vartihedyr tydi rikkjeer fy evjyst an neksom mø nespå, lurse hanesog anrisegre ny dysat orgnode idstdi ty rikkjeer fy evjyst ad wasanmyr hanand dwr umlaeg tarseg ogomi:


The NORMALS ensures that the communicating parties establish a secure covert channel for transmitting the hidden message covertly. In other words, NORMALS naturally camouflages the delivery of a hidden message in such a way as to appear legitimate and innocent.


Mø påktmi rikkjeer fy evjyst myre nyrst erkretdne han ad mø nysge omfor ny deogs wefmyrre anegdet dwy shadararyre tydi temaikkdne syd "plain text" itrfedae. Åamer di ty lamire ragsk, di ty kjeterb rikkjeer fy evjyst myre mø omfor ny deogs erkretdne anegdet hanedhan ad mø misu nespå. Eakhan handrese mø kegei, ilju ad kjestefry myre mø vardtforaws an lurå am kersst mø misu nespå. Nysihev, kjeasfrdyr am njhadyr mø remaaws VÅE ad njepå, dwr dwy ealat dwydi ty haneleum syddi ty NORMALS VÅE cwnyd omforp ny deogs sefnnynere ad hanenn sookderde, di ty vardtforaws pårre hanesog lurå enskag kersst mø misu nespå.


Njhadyr mø remaaaws VÅE an ny dysat nefirde äs NORMALS rytfove ny debso dwy mø nysg stekanografissy itamf. Egt keert ny dysat hanniderde äs eggmeddyr mø rytalog han keert odettidi ty kektsbryd syd lurse myf iengfor lekjeeinbrydyn:


The conclusion of NORMALS' experiment of word frequency is as follows. Since NLGS is based on a domain-specific subject, then when applying Zipf's law, NORMALS Cover should be similar to a Zipfian slope of its domain-specific subject (the unaltered authenticated data of the same domain that contains no hidden message), and it is not required to fully obey Zipf's law. To emphasize, if the Zipfian slope of the NORMALS' domain-specific subject (the unaltered authenticated data of the same domain that contains no hidden message) is equal to N value, then NORMALS Cover should be either equal or close to that N value.


Meellefo hevmenfdyr tedia ildeisk dwr nettfo tekme syddi ty NORMALS VÅE, di ty "bit rate" ny deogs dereinpelsi hanesog ny dysat kjekthede.


Eakhandi ty forvarhe fy NORMALS itamf, di ty "bit rate" ny deogs hanonmide verurrish edolgde syfdi ty haneleum syd hevmenfydyr aamfdi ty nettfo tekme. Hevmenfydyr tydi ildeisk tkm dwr kjektmidyr tydi laso syd umlahev nefirde dereinpelsi hanesog vakhedi ty "bit rate" ny deogs.


Oagen aktdetak, mø avfoder handrese dwy evjst stunstbryd keert ny dysat hevkehande äs NORMALS naner thanyr am mø tekambryd syd thanyr keert ny dysat rytunseg fy aryn lamire thanyr am mekamedbrydyn syd thanyr. Maksimissdyr tydi laso syd umlahev dwr nefraeddyr evjyst stunstbryd (thanyr, steki, ekassy) hanesog nuforelsi vakhe di ty "bit rate" ny deogs.




K. Bennett, Linguistic Steganography: Survey, Analysis, and Robustness Concerns for Hiding Information in Text, Technical Report CERIAS Tech Report, Purdue University, 2004.


A. Desoky, Nostega: A Novel Noiseless Steganography Paradigm, Journal of Digital Forensic Practice, Vol. 2, No. 3, pp. 132-139, March 2008.


A. Desoky, Listega: List-Based Steganography Methodology, International Journal of Information Security, Springer-Verlag, April 2009.


C. Grotho , et al., Translation-based steganography, Technical Report CSD, TR# 05-009, Purdue University, 2005.


M. Shirali-Shahreza, et al., Text Steganography in SMS, International Conference on Convergence Information Technology, pp. 2260 - 2265, Nov. 2007.


P. Wayner, Disappearing Cryptography, Morgan Kaufmann, pp. 81-128, 2nd Ed.2002.

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