NDLI: A Statistical Algorithm for Linguistic Steganography Detection Based on Distribution of Words

Content Provider	IEEE Xplore Digital Library
Author	Chen Zhi-li Huang Liu-sheng Yu Zhen-shan Li Ling-jun Yang wei
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei (Huang Liu-sheng; Yu Zhen-shan; Li Ling-jun; Yang wei)
Abstract	In this paper, a novel statistical algorithm for linguistic steganography detection, which takes advantage of distribution of words in the text segment detected, is presented. Linguistic steganography is the art of using written natural language to hide the very presence of secret messages. Using the text data, which is the foundational media in Internet communications, as its carrier, linguistic steganography plays an important part in Information Hiding (IH) area. The previous work was mainly focused on linguistic steganography and there were few researches on linguistic steganalisys. We attempt to do something to help to fix this gap. In our experiment of detecting the three different linguistic steganography methods: NICETEXT, TEXTO and Markov-chain-Based, the total accuracies on discovering stego-text segments and normal text segments are found to be 87.39% 95.51%, 98.50%, 99.15% and 99.57% respectively when the segment size is 5 kB, WkB, 20 kB, 30 kB and 40 kB. Our research shows that the linguistic steganalysis based on distribution of words is promising.
Starting Page	558
Ending Page	563
File Size	431690
Page Count	6
File Format	PDF
ISBN	9780769531021
DOI	10.1109/ARES.2008.61
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-04
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Availability Dictionaries detection statistical Natural languages linguistic steganalysis distribution of words Computer science Steganography linguistic steganography High performance computing Internet Cryptography Computer security National security
Content Type	Text
Resource Type	Article

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