Text steganography on RNN-Generated lyrics

We present a Recurrent Neural Network (RNN) Encoder-Decoder model to generate Chinese pop music lyrics to hide secret information. In particular, on a given initial line of a lyric, we use the LSTM model to generate the next Chinese character or word to form a new line. In so doing, we generate the...

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Main Authors: Yongju Tong, YuLing Liu, Jie Wang, Guojiang Xin
Format: Article
Language:English
Published: AIMS Press 2019-06-01
Series:Mathematical Biosciences and Engineering
Subjects:
Online Access:https://www.aimspress.com/article/10.3934/mbe.2019271?viewType=HTML
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author Yongju Tong
YuLing Liu
Jie Wang
Guojiang Xin
author_facet Yongju Tong
YuLing Liu
Jie Wang
Guojiang Xin
author_sort Yongju Tong
collection DOAJ
description We present a Recurrent Neural Network (RNN) Encoder-Decoder model to generate Chinese pop music lyrics to hide secret information. In particular, on a given initial line of a lyric, we use the LSTM model to generate the next Chinese character or word to form a new line. In so doing, we generate the entire lyric from what has been generated so far. Using common lyric formats and rhymes we extracted, we generate lyrics embedded with secret information to meet the visual and pronunciation requirements. We carry out experiments and theoretical analysis, and show that lyrics generated by our method offer higher embedding capacities for steganography, which also look more natural than the existing steganography methods based on text generations.
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spelling doaj.art-91bfdfea63a040a3968170ec74aced2a2022-12-22T02:55:24ZengAIMS PressMathematical Biosciences and Engineering1551-00182019-06-011655451546310.3934/mbe.2019271Text steganography on RNN-Generated lyricsYongju Tong0YuLing Liu1Jie Wang2Guojiang Xin31. College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China1. College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China2. Department of Computer Science, University of Massachusetts Lowell, Lowell, M.A., 01854, USA3. College of Management and Information Engineering, Hunan University of Chinese Medicine, Changsha 410208, ChinaWe present a Recurrent Neural Network (RNN) Encoder-Decoder model to generate Chinese pop music lyrics to hide secret information. In particular, on a given initial line of a lyric, we use the LSTM model to generate the next Chinese character or word to form a new line. In so doing, we generate the entire lyric from what has been generated so far. Using common lyric formats and rhymes we extracted, we generate lyrics embedded with secret information to meet the visual and pronunciation requirements. We carry out experiments and theoretical analysis, and show that lyrics generated by our method offer higher embedding capacities for steganography, which also look more natural than the existing steganography methods based on text generations.https://www.aimspress.com/article/10.3934/mbe.2019271?viewType=HTMLtext steganographylyric generationrecurrent neural networkschar-rnnword-rnn
spellingShingle Yongju Tong
YuLing Liu
Jie Wang
Guojiang Xin
Text steganography on RNN-Generated lyrics
Mathematical Biosciences and Engineering
text steganography
lyric generation
recurrent neural networks
char-rnn
word-rnn
title Text steganography on RNN-Generated lyrics
title_full Text steganography on RNN-Generated lyrics
title_fullStr Text steganography on RNN-Generated lyrics
title_full_unstemmed Text steganography on RNN-Generated lyrics
title_short Text steganography on RNN-Generated lyrics
title_sort text steganography on rnn generated lyrics
topic text steganography
lyric generation
recurrent neural networks
char-rnn
word-rnn
url https://www.aimspress.com/article/10.3934/mbe.2019271?viewType=HTML
work_keys_str_mv AT yongjutong textsteganographyonrnngeneratedlyrics
AT yulingliu textsteganographyonrnngeneratedlyrics
AT jiewang textsteganographyonrnngeneratedlyrics
AT guojiangxin textsteganographyonrnngeneratedlyrics