On January 6, the Washington Headquarters Services (WHS) posted a request for information (RFI) entitled Zero Trust Assessments & Artificial Intelligence. Responses are due by 12:00 p.m. Eastern on February 9.
The Zero Trust Portfolio Management Office (ZT PfMO) within the DoD Chief Information Officer (CIO) is the office responsible for the overall DoD ZT lead to coordinate, synchronize, and advance the DoD Enterprise into a ZT cybersecurity architecture, modernizing the DoD’s ability to prevent malicious actors from exploiting DoD data and resources. Scaling ZT assessments to encompass the entirety of the DoD enterprise, while maintaining accuracy and efficiency, necessitates innovative approaches that leverage automation and advanced technologies. As such, the DoD is interested in understanding how emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML) can be leveraged to automate and enhance the Zero Trust assessment process.
This RFI seeks information from vendors on Commercial Off-the-Shelf platforms and services that leverage automation, AI and ML to accelerate and scale ZT assessments across the DoW enterprise. This will address anticipated capacity limitations and support continuous assessment for validating compliance with Target Level Zero Trust milestones. This RFI is for market research purposes only and does not constitute a solicitation.
The DoW seeks industry perspectives on leveraging automation and AI to accelerate and scale DoW-led ZT Purple Team (a collaborative security assessment approach where the red team, blue team, and system owners work together) evaluations of ZT environments on UNCLASSIFIED and SECRET networks. These evaluations will assess the proper implementation of core Zero Trust requirements for adequacy and efficiency, while identifying limitations, compliance failures, and facilitating continuous assessment requirements for the 91 Target level Zero Trust Activities and the ten Zero Trust Acceptance Criteria.
Review the WHS zero trust and AI RFI.
Source: SAM
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