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The Risk Management Framework (RMF) is a United States federal government guideline, standard, and process for managing risk to help secure information systems (computers and networks). The RMF was developed by the National Institute of Standards and Technology (NIST), and provides a structured process that integrates information security ...
Although re-accreditations via DIACAP continued through late 2016, systems that had not yet started accreditation by May 2015 were required to transition to the RMF processes. [1] The DoD RMF aligns with the National Institute of Standards and Technology (NIST) Risk Management Framework (RMF). [2] [3]
NIST Special Publication 800-37 Rev. 1 was published in February 2010 under the title "Guide for Applying the Risk Management Framework to Federal Information Systems: A Security Life Cycle Approach". This version described six steps in the RMF lifecycle. Rev. 1 was withdrawn on December 20, 2019 and superseded by SP 800-37 Rev. 2. [1]
Guide to NIST: Author: Covahey, Virginia: Software used: Digitized by the Internet Archive: Conversion program: Recoded by LuraDocument PDF v2.65: Encrypted: no: Page size: 594 x 777 pts; 569 x 769 pts; 566 x 750 pts; 568 x 769 pts; 568 x 751 pts; 566 x 752 pts; 567 x 751 pts; 585 x 761 pts; 576 x 766 pts; 602 x 772 pts; Version of PDF format: 1.5
NIST had an operating budget for fiscal year 2007 (October 1, 2006 – September 30, 2007) of about $843.3 million. NIST's 2009 budget was $992 million, and it also received $610 million as part of the American Recovery and Reinvestment Act. [18] NIST employs about 2,900 scientists, engineers, technicians, and support and administrative personnel.
A public draft of Version 1.1 was released for comment in 2017, and the final version was published on April 16, 2018. Version 1.1 retained compatibility with the original framework while introducing additional guidance on areas such as supply chain risk management.
An AI Safety Institute (AISI), in general, is a state-backed institute aiming to evaluate and ensure the safety of the most advanced artificial intelligence (AI) models, also called frontier AI models. [1] AI safety gained prominence in 2023, notably with public declarations about potential existential risks from AI.
eMASS is a service-oriented computer application that supports Information Assurance (IA) program management and automates the Risk Management Framework (RMF). [1] The purpose of eMASS is to help the DoD to maintain IA situational awareness, manage risk, and comply with the Federal Information Security Management Act (FISMA 2002) and the Federal Information Security Modernization Act (FISMA ...