基于Hopfield神经网络的文本认证与同义词替换的可恢复水印算法

摘要

Aiming at problems of tamper detection and recovery, a recoverable watermarking algorithm for text authentication and synonym replacement based on synonym replacement technology and associative memory function of Hopfield neural network is proposed. The text is divided into replaceable synonyms and non-replaceable words. The feature information of replaceable synonyms is extracted according to the position in their thesaurus and the feature information of non-replaceable words is extracted according to the structure and stroke of Chinese characters in the text. Then, the watermark is embedded by synonym replacement. The information of watermark and the feature information of non-replaceable words are input into the Hopfield neural network and they are trained to realize tamper detection and recovery function of replaceable synonyms. The simulation results show that the proposed algorithm has good robustness, tamper detection performance and recoverability, and by this algorithm, tamper detection and the location of replaceable synonyms and non-replaceable words are implemented to realize text authentication, recover the original replaceable synonyms and achieve recovery.%针对水印文本的篡改检测和恢复问题，利用Hopfield网络的联想记忆功能，提出一种Hopfield神经网络与同义词替换技术相结合的文本认证与同义词替换的可恢复水印算法。算法首先将文本分为可替换同义词和非替换词语，利用可替换同义词在其同义词库中的位置及汉字笔画和结构特征，分别提取文本可替换同义词的特征信息和非替换词语的特征信息。然后通过同义词替换实现水印嵌入，并将水印信息和非替换词语的特征信息输入Hopfield神经网络进行训练，实现篡改检测与可替换同义词的恢复功能。实验仿真表明，该算法具有较好的鲁棒性、篡改检测性和恢复能力，能篡改检测和定位可替换同义词、非替换词语，实现认证功能，且能恢复被替换的同义词，实现恢复功能。