Context-Aware Data Loss Prevention for Cloud Storage Services

Abstract

With the wide adoption of hybrid cloud, there are many potential risks that need to be mitigated to ensure that the utilizations of services are at their optimal levels. One of the major risks that has garnered much attention is maintaining maximum security and confidentiality for sensitive information. Detecting sensitive content at near real-time and at cloud scale has become a critical first step for organizations to prevent data loss and comply with data privacy laws and regulations. Proactive detection raises security awareness at the early stage and thus can be used to govern how the information should be managed, protected, and utilized in the hybrid cloud. In contrast to traditional dictionary or policy-based approaches, we introduce a system that detects sensitive content by leveraging its semantic contextual information through various machine learning and deep learning techniques at different levels of granularity within the document, and is the first of its kind.