Automatic Declassification of Textual Documents by Generalizing Sensitive Terms

With the advent of internet, large numbers of text documents are published and shared every day . Each of these documents is a collection of vast amount of information. Publically sharing of some of this information may affect the privacy of the document, if they are confidential information. So before document publishing, sanitization operations are performed on the document for preserving the privacy and inorder to retain the utility of the document. Various schemes were developed to solve this problem but most of them turned out to be domain specific and most of them didn't consider the presence of semantically correlated terms. This paper presents a generalized sanitization method that discovers the sensitive information based on the concept of information content. The proposed method removes the confidential information from the text document by first finding the independent sensitive terms. Then with the use of these sensitive terms the correlated terms that cause a disclosure threat are discovered. Again with the help of a generalization algorithm these sensitive and correlated terms with high disclosure risk are generalized.