Privacy Preservation and Detection of Sensitive Data Exposure over Cloud

Abstract: Statistics from security firms, research institutions and government organizations show that the number of data-leak instances have grown rapidly increases years. Among various data-leak cases, human mistakes are one of the main causes of data loss. There exist solutions detecting inadvertent sensitive data leaks caused by human mistakes and to provide alerts for organizations. A common approach is to screen content in storage and transmission for exposed sensitive information. Such an approach usually requires the detection operation to be conducted in secrecy. However, this secrecy requirement is challenging to satisfy in practice, as detection servers may be compromised or outsourced. In this paper, we present a privacy preserving data-leak detection solution to solve the issue where a special set of sensitive data digests is used in detection. The advantage of our method is that it enables the data owner to safely delegate the detection operation to a semi honest provider without revealing the sensitive data to the provider. We describe how Internet service providers can over their customers DLD as an add-on service with strong privacy guarantees. The evaluation results show that our method can support accurate detection with very small number of false alarms under various data leak.

Keywords: Data leak, network security, privacy.