NIST Big Data Interoperability Framework: Volume 4, Security and Privacy
Wo L. Chang, Arnab Roy, Mark Underwood
Big Data is a term used to describe the large amount of data in the networked, digitized, sensor-laden, information-driven world. While opportunities exist with Big Data, the data can overwhelm traditional technical approaches and the growth of data is outpacing scientific and technological advances in data analytics. To advance progress in Big Data, the NIST Big Data Public Working Group (NBD-PWG) is working to develop consensus on important, fundamental concepts related to Big Data. The results are reported in the NIST Big Data Interoperability Framework (NBDIF) series of volumes. This volume, Volume 4, contains an exploration of security and privacy topics with respect to Big Data. The volume considers new aspects of security and privacy with respect to Big Data, reviews security and privacy use cases, proposes security and privacy taxonomies, presents details of the Security and Privacy Fabric of the NIST Big Data Reference Architecture (NBDRA), and begins mapping the security and privacy use cases to the NBDRA.
Big Data characteristics, Big Data forensics, Big Data privacy, Big Data risk management, Big Data security, Big Data taxonomy, computer security, cybersecurity, encryption standards, information assurance, information security frameworks, role-based access controls, security and privacy fabric, use cases.
, Roy, A.
and Underwood, M.
NIST Big Data Interoperability Framework: Volume 4, Security and Privacy, Special Publication (NIST SP), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.SP.1500-4r2
(Accessed May 16, 2021)