The Mask of ZoRRo: preventing information leakage from documents
In today’s enterprise world, information about business entities such as a customer’s or patient’s name, address, and social security number is often present in both relational databases as well as content repositories. Information about such business entities is generally well protected in databases by well-defined and fine-grained access control. However, current document retrieval systems do not provide user-specific, fine-grained redaction of documents to prevent leakage of information about business entities from documents. Leaving companies with only two choices: either providing complete access to a document, risking potential information leakage, or prohibiting access to the document altogether, accepting potentially negative impact on business processes. In this paper, we present ZoRRo, an add-on for document retrieval systems to dynamically redact sensitive information of business entities referenced in a document based on access control defined for the entities. ZoRRo exploits database systems’ fine-grained, label-based access-control mechanism to identify and redact sensitive information from unstructured text, based on the access privileges of the user viewing it. To make on-the-fly redaction feasible, ZoRRo exploits the concept of $$k$$k-safety in combination with Lucene-based indexing and scoring. We demonstrate the efficiency and effectiveness of ZoRRo through a detailed experimental study.