LinL:Lost in n-best list

Peng Meng, Yun Qing Shi, Liusheng Huang, Zhili Chen, Wei Yang, Abdelrahman Desoky

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Translation-based steganography (TBS) is a new kind of text steganographic scheme. However, contemporary TBS methods are vulnerable to statistical attacks. Differently, this paper presents a novel TBS, namely Lost in n-best List, abbreviated as LinL, that is resilient against the current statistical attacks. LinL employs only one Statistical Machine Translator (SMT) in the encoding process which selects one of the n-best list of each cover text sentence in order to camouflage messages in stegotext. The presented theoretical analysis demonstrates that there is a classification accuracy upper bound between normal translated text and the stegotext. When the text size is 1000 sentences, the theoretical maximum classification accuracy is about 60%. The experiment results also show current steganalysis methods cannot detect LinL.

Original languageEnglish (US)
Title of host publicationInformation Hiding - 13th International Conference, IH 2011, Revised Selected Papers
Pages329-341
Number of pages13
DOIs
StatePublished - 2011
Event13th International Conference on Information Hiding, IH 2011 - Prague, Czech Republic
Duration: May 18 2011May 20 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6958 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Conference on Information Hiding, IH 2011
CountryCzech Republic
CityPrague
Period5/18/115/20/11

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Keywords

  • LinL
  • linguistic steganography
  • natural language steganography
  • text steganography
  • translation-based steganography (TBS)

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