Security and Privacy of Big Data - A NIST Perspective
The NIST Big Data Interoperability Framework: Volume 4, Security and Privacy document was prepared by the NIST Big Data Public Working Group (NBD-PWG) Security and Privacy Subgroup to identify security and privacy issues that are specific to Big Data.
Big Data application domains include health care, drug discovery, insurance, finance, retail and many others from both the private and public sectors. Among the scenarios within these application domains are health exchanges, clinical trials, mergers and acquisitions, device telemetry, targeted marketing and international anti-piracy. Security technology domains include identity, authorization, audit, network and device security, and federation across trust boundaries.
Clearly, the advent of Big Data has necessitated paradigm shifts in the understanding and enforcement of security and privacy requirements. Significant changes are evolving, notably in scaling existing solutions to meet the volume, variety, velocity, and variability of Big Data and retargeting security solutions amid shifts in technology infrastructure (e.g., distributed computing systems and non-relational data storage.) In addition, diverse datasets are becoming easier to access and increasingly contain personal content. A new set of emerging issues must be addressed, including balancing privacy and utility, enabling analytics and governance on encrypted data, and reconciling authentication and anonymity.
With the key Big Data characteristics of variety, volume, velocity, and variability in mind, the Subgroup gathered use cases from volunteers, developed a consensus-based security and privacy taxonomy, related the taxonomy to the NIST Big Data Reference Architecture (NBDRA), and validated the NBDRA by mapping the use cases to the NBDRA.
In this talk, I will present the current status of the work and focus on how it is expected to inform architectural decisions for fortifying service provider infrastructure.