Research On Natural Language Text Steganography Based On Multiple Rules

With the rapid development of information science and industry dominated by computer science and network technology,information security problems such as eavesdropping,replay,denial,information leakage,and illegal use are becoming increasingly prominent.Compared with the traditional information encryption technology,steganography can protect important information in a more covert way.Steganography is usually done with a carrier with a large amount of redundancy,such as images,audio,video,etc.As the oldest and most used media,the text is difficult to carry too much secret information due to its small redundancy,but it is also more valuable for research.In this thesis,we take natural language text as the research object of steganography and study the steganography methods of natural language text from different perspectives.The specific research contents and achievements are as follows:(1)The text information steganography method based on variable grammar rules is studied.In our research,we found that different dimensional grammar models capture different features of the training text during the construction process,which affects the quality of the final steganography text.Therefore,we combine different dimensional grammar models to take advantage of the advantages of different dimensional grammar models.In the research,we proposed two different steganography models of mixed grammatical rules based on this idea,namely,the text information steganography method based on half frequency crossover rule and the text information steganography method based on multi-rule language models alternation.Both of these methods try to complete the generation of steganography text based on more flexible language relations,hoping to achieve better steganography effect.We have completed the modeling of the proposed method and selected different types of data for experiments to verify the effectiveness of the method.(2)The text information steganography method based on transition probability isstudied.In the research,we highlight the role of transition probability in Markov chain state transition diagram and propose three different steganography methods based on this idea.Firstly,the text information steganography method based on state transition binary sequence is proposed.In this method,we not only design the steganography model around the concept of transition probability in Markov chain but also encrypt some important information in the process of information communication to further strengthen the communication security of information.Secondly,we propose the text information steganography method based on the single bit rule to select the optimal and suboptimal language sequences in the model,aiming to preserve the better language features in the text to guide the generation of steganography text.Finally,we propose the text information steganography method based on the variable bit rule,which preserves the linguistic features of the training text to the greatest extent,to achieve the best text steganography effect.We have completed the modeling of the proposed method and selected different types of data for experiments to verify the effectiveness of the method.(3)The text information steganography method based on improved evaluation index is studied.In the process of further research,we find that it is not objective and comprehensive to evaluate the quality of text only based on the transition probability in Markov chain state transition diagram.In general texts,the longer the length of the language sequence,the lower the frequency of the language sequence.These long language sequences may have good language features and quality,and they are deleted from the language model just because of their low frequency of occurrence,which has a negative impact on the quality of the model.Therefore,we propose the text information steganography method based on improved evaluation index and single bit rule.This method can evaluate the quality of text more objectively and achieve better performance by establishing a new evaluation standard of sentence quality and the establishment benchmark of model.We have completed the modeling of the proposed method and selected different types of data for experiments to verify the effectiveness of the method.At the end of the thesis,the research work is summarized,and the future work direction and content are prospected.