Biblio

Redaction of personal, confidential and sensitive information from documents is becoming increasingly important for individuals and organizations. In past years, there have been many well-publicized cases of data leaks from various popular companies. When the data contains sensitive information, these leaks pose a serious threat. To protect and conceal sensitive information, many companies have policies and laws about processing and sanitizing sensitive information in business documents.The traditional approach of manually finding and matching millions of words and then redacting is slow and error-prone. This paper examines different models to automate the identification and redaction of personal and sensitive information contained within the documents using named entity recognition. Sensitive entities example person’s name, bank account details or Aadhaar numbers targeted for redaction, are recognized based on the file’s content, providing users with an interactive approach to redact the documents by changing selected sensitive terms.