AWS Public Sector Blog
Category: Security
ZTAG-I, a reference zero trust architecture for the US federal government
In this blog, we introduce AWS Zero Trust Accelerator for Government – Integrated (ZTAG-I), a reference architecture that aligns with federal zero trust guidance. ZTAG-I accelerates adoption of zero trust architecture by providing a tested example of a fully integrated technology stack that solves key challenges that arise when adopting zero trust.
AWS achieves U.S. Department of Defense’s CMMC Level 2 certification for Controlled Working Environment
AWS has achieved the U.S. Department of Defense’s (DoD) Cybersecurity Maturity Model Certification (CMMC) Level 2 certification for the Controlled Working Environment (CWE). This certification enhances our DoD contract support capabilities and demonstrates our cybersecurity commitment.
University of British Columbia Cloud Innovation Centre: Prototyping generative AI solutions using AWS
The University of British Columbia (UBC) Cloud Innovation Centre (CIC) has become a hub for innovation by prototyping generative AI applications in collaboration with public sector sponsors. This post highlights how the UBC CIC uses AWS to accelerate generative AI development, sharing lessons learned, tools used, and actionable insights you can apply to your projects.
How public safety agencies can meet AI data security requirements
In this post, we discuss the crucial factors public safety agencies should consider when choosing a generative AI provider and explain how AWS can enable a secure, protected system.
Security best practices that accelerate nonprofit mission impact
Nonprofit organizations face unique security challenges due to their resource constraints and prioritization of mission-focused initiatives. In this blog post, we discuss Amazon Web Services (AWS) security best practices to accelerate mission impact and demonstrate how upfront security investments can both improve security and save time on redundant processes in the long run.
Enhancing decision making for system changes with generative AI
In this post, we explore an innovative solution—developed by Booz Allen, an Amazon Web Services (AWS) Premier Services Partner—that uses Amazon Bedrock-powered generative artificial intelligence (AI) to enhance the decision-making process for system changes.
AWS Marketplace assessed ‘Awardable’ for DoD work in the P1 Solutions Marketplace
Amazon Web Services (AWS) is pleased to announce that AWS Marketplace has received “Awardable” status in the Department of Defense (DoD) Platform One (P1) Solutions Marketplace. This designation enables DoD organizations to readily access and procure solutions through AWS Marketplace using established acquisition pathways.
Self-hosting source code of the Landing Zone Accelerator on AWS
Some customers using Amazon Web Services (AWS) prohibit users from installing software from public sources. Recently, the Landing Zone Accelerator on AWS (LZA) solution added optional capabilities to support this use case. Instead of installing directly from the public LZA GitHub repository, which is the default installation path for most customers, LZA can be self-hosted from your own Amazon Simple Storage Service (Amazon S3) bucket. This post shows the technical steps necessary to install LZA using Amazon S3.
Securely onboarding countries to the AWS Cloud
In an increasingly digital world, governments and public sector entities are seeking secure and efficient ways to use cloud technologies. As we’ve innovated and expanded the Amazon Web Services (AWS) Cloud, we continue to prioritize making sure customers are in control and able to meet their national regulatory requirements. In this post, we share how AWS is collaborating with national cyber regulators and other public sector entities to enable secure adoption of the AWS Cloud across countries’ public sectors.
Securely running AI algorithms for 100,000 users on private data
This post explores the architectural design and security concepts employed by Radboud University Medical Center Nijmegen (Radboudumc) to build a secure artificial intelligence (AI) runtime environment on Amazon Web Services (AWS). Business leaders dealing with sensitive or regulated data will find this post invaluable because it demonstrates a proven approach to using the power of AI while maintaining strict data privacy and security standards.