Attack Tolerant Big Data File System

Data driven decisions derived from big data have assumed critical importance in many application domains, fueling the demand for collection, transportation, storage and processing of massive volumes of data at fast speeds. Such applications have made data a valuable resource that needs to be provided appropriate security. High value associated with big data sets has rendered the entire cyber infrastructure, which includes big data storage systems, attractive targets for cyber attackers. Attackers are constantly trying to mount attacks on the cyber infrastructure, including data storage systems, to compromise the Confidentiality, Integrity and Availability of data and information. Common defense strategy that has been mostly employed to protect cyber assets involves first taking preventive measures, and if these fail, detecting intrusions and finally recovery. Unfortunately, attackers have developed tremendous technical sophistication to defeat most defensive mechanisms. Alternative strategy is to design architectures which are intrinsically attack tolerant. This paper describes a strategy that involves eliminating single point of security failures through fragmentation, coding, dispersion and reassembly. It is shown that this strategy can be successfully applied to networked big data file systems to make them tolerant to multiple cyber attacks.