期刊论文

Zhu, Chengzhang

英文

Mathematics

2227-7390

2020

8

9

10.3390/math8091558

National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61972057, U1836208]; Hunan Provincial Natural Science Foundation of ChinaNatural Science Foundation of Hunan Province [2019JJ50655, 2020JJ4624]; Scientific Research Fund of Hunan Provincial Education Department of ChinaHunan Provincial Education Department [18B160, 19A020]; Open Fund of Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle Infrastructure Systems (Changsha University of Science and Technology) [kfj180402]; "Double First-class" International Cooperation and Development Scientific Research Project of Changsha University of Science and Technology [2018IC25]

本校为第一机构

With the development of natural language processing, linguistic steganography has become a research hotspot in the field of information security. However, most existing linguistic steganographic methods may suffer from the low embedding capacity problem. Therefore, this paper proposes a character-level linguistic steganographic method (CLLS) to embed the secret information into characters instead of words by employing a long short-term memory (LSTM) based language model. First, the proposed method utilizes the LSTM model and large-scale corpus to construct and train a character-level text gene...