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Nvidia’s latest product strategy updates announced last week at the March 2022 GPU Technology Conference (GTC) reflect the high priority their devops and engineering teams are placing on closing the growing gaps in data center cybersecurity. Gaps in cybersecurity tech stacks are purportedly growing because the platforms supporting them typically were not designed for a zero-trust world

The lack of platform and tech stack support makes implementing least-privileged access across data centers to the server level financially unattainable for many IT budgets. Additionally, getting microsegmentation accomplished across legacy servers and integrating identity access management (IAM) takes longer on legacy tech stacks. Likewise, implementing privileged access management (PAM) across a legacy infrastructure environment often requires integration workarounds. 

Top-down approaches to equipping legacy tech stacks with the technology needed to support zero trust can be hard to do well. Nvidia’s product and solution strategies, unveiled at GTC 2022, seem to underscore that the company understands this and is taking aim at the opportunity to solve complex tech stack challenges and grow its total available market simultaneously.

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Nvidia’s rapid platform progress on cybersecurity 

VMware’s Project Monterey, which is supported by Nvidia’s BlueField-2 DPU (currently in Beta) reflects how ingrained the design goal of augmenting enterprise tech stacks are in their product strategy. For example, the Nvidia Bluefield-3 DPU programmable data center infrastructure-on-a-chip has a public key accelerator (PKA), root-of-trust, security firmware updates, flash encryption and Cerberus compliance designed into their silicon and network platforms. All features that work together to enhance security efforts. Specifically, the  Monterey LaunchPad Beta is flexible enough in design to support microsegmentation across a data center, which is a core requirement for implementing a zero-trust framework.

Nvidia’s strategy of looking for gaps in enterprise tech stacks and closing them with rapid GPU R&D coupled with new DOCA releases is working in cybersecurity.

Also announced at last week’s conference, Nvidia’s Hopper GPU architecture and new H100 GPU, has confidential computing support designed to secure data and models. The H100 GPU also reflects company-wide design goals focused on enabling greater zero-trust across all products. Its confidential computing capabilities are designed to protect AI models and customer data while in process. 

Confidential computing isolates data in an encrypted area during processing. The contents of the encrypted area, including data being processed, are accessible only to authorized programming code and are invisible to anyone else. 

The Nvidia AI platform also proves pivotal in enabling enterprises to close gaps in their cybersecurity tech stacks. It’s used in over 25,000 companies worldwide. Nvidia’s AI Enterprise 2.0 cloud-native suite of AI and data analytics tools and frameworks, optimized and certified by the company and supported across every major data center and cloud platform. 

“We updated 60 SDKs (software development kits) at this GTC,” said Jensen Huang, Nvidia’s CEO “For our 3 million developers, scientists and AI researchers and tens of thousands of startups and enterprises, the same Nvidia systems you run just got faster.” 

Given how ingrained cybersecurity and zero trust are within Nvidia’s devops design goals, the company provides the tools customers need to close gaps in their tech stacks that put them at risk. 

National standards aim to create benchmarks for zero trust architecture

Nearly every CISO and CIO have preferred benchmarking approaches and assessing how much a given vendors’ solution reduces risk and secures their business. Organizations ideally should benchmark how effective Nvidia is in assisting them at reaching their zero trust initiatives. Currently, a growing base of new benchmarks and frameworks is being created for CISOs, CIOs and their teams in this area.

One of the primary catalysts driving the development of these essential benchmarks is the National Security Telecommunications Advisory Committee’s (NSTAC) report, Zero Trust and Trusted Identity Management

President Biden’s Executive Order 14028: Improving the Nation’s Cybersecurity defines zero trust architecture as the cybersecurity standard across all government agencies. It relies on on the latest National Institute of Standards and Technology (NIST) zero trust architecture standard (NIST 800-207: Zero Trust Architecture). 

As a supplement to the above, the president’s office of management and budget’s  Federal Zero Trust Strategy has pragmatic, useful insights any organization can use for planning their zero trust initiatives.The Department of Defense (DoD) Zero Trust Reference Architecture also provides a useful taxonomy for organizing each area of a zero-trust security strategy.

Of the many maturity models created since EO 14028 was signed, one of the most valuable is from the Cybersecurity & Infrastructure Security Agency (CISA). Unlike many vendor-based models that could be biased towards a given technology or deployment methodology, CISA has strived to create an impartial, fair model that can span an enterprise’s five core security dimensions. The CISA Zero Trust Maturity Model provides insights into traditional, advanced and optimal levels of zero trust maturity. It’s a useful framework for CISOs and CIOs to communicate roadmap goals from a long-term or strategic standpoint. 

CISA’s Maturity Model can help benchmark the contributions Nvidia’s latest technologies make to zero trust initiatives across organizations. 

Filling gaps in the tech stack

Nvidia excels at finding gaps in tech stacks, then engineering new solutions from silicon to SDKs to solve them. The company’s  rapid advances in zero-trust security are a case in point. Last week at GTC 2022, Nvidia DOCA 1.3 was launched along with updates to 60 different SDKs to streamline the development efforts of partners, startups and enterprises standardizing on the Nvidia AI platform. In addition, their reliance on Nvidia Morpheus, their continuously learning cybersecurity framework, continues to gain adoption across data centers. 

It is technologies like these, that Nvidia continues to strive to be at the forefront of, that will assist enterprise leaders and security teams with adhering to and implementing national guidelines laid out by government entities.

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