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LinL:Lost in n-best list

  • Peng Meng*
  • , Yun Qing Shi
  • , Liusheng Huang
  • , Zhili Chen
  • , Wei Yang
  • , Abdelrahman Desoky
  • *此作品的通讯作者
  • University of Science and Technology of China
  • New Jersey Institute of Technology
  • University of Maryland, Baltimore County

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

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.

源语言英语
主期刊名Information Hiding - 13th International Conference, IH 2011, Revised Selected Papers
329-341
页数13
DOI
出版状态已出版 - 2011
已对外发布
活动13th International Conference on Information Hiding, IH 2011 - Prague, 捷克共和国
期限: 18 5月 201120 5月 2011

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
6958 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议13th International Conference on Information Hiding, IH 2011
国家/地区捷克共和国
Prague
时期18/05/1120/05/11

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