{"title":"Cloud Model Based Zero-Watermarking Algorithm for Authentication of Text Document","authors":"Xitong Qi, Yuling Liu","doi":"10.1109/CIS.2013.155","DOIUrl":null,"url":null,"abstract":"Content authentication of text document has become a major concern in the current digital era. In this paper, a zero-watermark algorithm is proposed for Chinese text documents content authentication. Firstly, the frequencies of different part-of-speech (POS) tags are obtained through natural language processing technology. And they are used to calculate the expect value and entropy, which can be as text features. Then a watermark is generated by one-dimensional forward cloud model generator using the expect value and entropy. The watermark is sent to be registered and stored in the trusted third party called Certificate Authority (CA). If authentication is necessary, we calculate the similarity between the watermark of disputed text and its watermark registered in CA. Experimental results show that the algorithm is robust against content-preserving attacks while sensitive to malicious tampering.","PeriodicalId":294223,"journal":{"name":"2013 Ninth International Conference on Computational Intelligence and Security","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Ninth International Conference on Computational Intelligence and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2013.155","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Content authentication of text document has become a major concern in the current digital era. In this paper, a zero-watermark algorithm is proposed for Chinese text documents content authentication. Firstly, the frequencies of different part-of-speech (POS) tags are obtained through natural language processing technology. And they are used to calculate the expect value and entropy, which can be as text features. Then a watermark is generated by one-dimensional forward cloud model generator using the expect value and entropy. The watermark is sent to be registered and stored in the trusted third party called Certificate Authority (CA). If authentication is necessary, we calculate the similarity between the watermark of disputed text and its watermark registered in CA. Experimental results show that the algorithm is robust against content-preserving attacks while sensitive to malicious tampering.