Poster:Winover Enterprise Dark Data

Any persistent untagged, untapped and unclassified data can be termed as dark data. It has two common traits: first, it is not possible to determine its worth, and second, in most of the scenarios it is inadequately protected. Previous work and existing solutions are restricted to cater single node system. Moreover, they perform specialized processing of selected content, for example, logs. Further, there is total negligence of stakeholders and minimal focus on the data getting generated within the enterprise. From the perspective of an enterprise it is important to understand the distribution, nature and worth of dark data, as it helps in choosing right security controls, insurance or steps needed to pre-process a system before discarding it.In this paper we demonstrate a distributed system, called File WinOver, for File Lifecycle Management (FLM). The solution operates in a distributed environment where it identifies the dormant and active files on a system, filters them as per requirement and computes their fingerprint. Moreover, the content fingerprinting is utilized to detect closed user groups. After which, it classifies the content based on configured policies, and maps them with the stakeholders. This mapping is further used for valuating the risk exposure of the file. Thus, our system helps in identifying dark data and assigns quantitative risk value.