Title :
Linguistic Steganography Detection Algorithm Using Statistical Language Model
Author :
Meng, Peng ; Hang, Liusheng ; Yang, Wei ; Chen, Zhili ; Zheng, Hu
Author_Institution :
Dept. of Comput. Sci. & Technol., Nat. High Performance Comput. Center at Hefei, Hefei, China
Abstract :
Steganography is a technique for embedding secret messages into carriers. Linguistic steganography is a branch of text steganography. Research on attacking methods against linguistic steganography plays an important role in information security (IS) area. In this paper, a linguistic steganography detecting algorithm using statistical language model (SLM) is presented. An experiment to detect text segments generated by linguistic steganography systems NICETEXT, TEXTO and Markov-chain-based is carried out. The result of our experiment shows when the text segment size is 2K and 5K, the detecting accuracies are found to be 93.9% and 96.3% respectively.
Keywords :
Markov processes; computational linguistics; natural language processing; security of data; statistical analysis; steganography; text analysis; Markov chain; NICETEXT; TEXTO; information security; linguistic steganography detection algorithm; statistical language model; text steganography; Computer science; Cryptography; Detection algorithms; High performance computing; Information security; Information technology; Natural languages; Steganography; Testing; Training data; Perplexity; Statistical Language Model(SLM); Steganalysis; Steganography; Text Processing;
Conference_Titel :
Information Technology and Computer Science, 2009. ITCS 2009. International Conference on
Conference_Location :
Kiev
Print_ISBN :
978-0-7695-3688-0
DOI :
10.1109/ITCS.2009.246
