Key Stroke Profiling for Data Loss Prevention

Data leakage has become a serious problem to many organizations. To provide visibility into what data is confidential and where it´s stored, many of current data leakage prevention (DLP) solutions depend on scanning file content. This approach needs the capability of parsing various file formats, but for those unsupported file formats there still exist risks of data breach. To address this issue, this study proposes an active DLP model by hooking on keyboard API to track and profile user key stroke behaviour. This has two major advantages: (1) It can discover sensitive data without parsing file formats, and (2) A data creator can be identified according to his/her key stroke behaviour. Since this model is based on key stroke profiling, it can resolve unsupported file format issue and have the capability of file creator identification.