The 16 members of the NIST-managed Internet of Things (IoT) Advisory Board have completed their report on barriers to the U.S. receiving the benefits of IoT adoption, along with their recommendations for overcoming those barriers. As Benson Chan (Chair) and Dan Caprio (Vice Chair) of the IoT Advisory Board state in the report: “The United States is in the early stages of a profound transformation, one that is driven by economic, societal, and cultural innovations brought about by the IoT. These innovations intertwine connectivity and digital innovation with the opportunity to drive a

This blog is part of a larger NIST series during the month of October for Cybersecurity Awareness Month , called 'Staff Stories Spotlight.' Throughout the month of October this year, Q&A style blogs will be published featuring some of our unique staff members who have interesting backgrounds, stories to tell, and projects in the world of cybersecurity. This year’s Cybersecurity Awareness Month theme is ‘Secure our World.’ How does this theme resonate with you, as someone working in cybersecurity? Everyone has the power to protect information. Like safety – where everyone’s responsibility is to

This blog is part of a larger NIST series during the month of October for Cybersecurity Awareness Month , called 'Staff Stories Spotlight.' Throughout the month of October this year, Q&A style blogs will be published featuring some of our unique staff members who have interesting backgrounds, stories to tell, and projects in the world of cybersecurity. This year’s Cybersecurity Awareness Month theme is ‘Secure our World.’ How does this theme resonate with you, as someone working in cybersecurity? Now more than ever, the use of technology is central to our lives. It is the means by which we are

This blog is part of a larger NIST series during the month of October for Cybersecurity Awareness Month , called 'Staff Stories Spotlight.' Throughout the month of October this year, Q&A style blogs will be published featuring some of our unique staff members who have interesting backgrounds, stories to tell, and projects in the world of cybersecurity. This year’s Cybersecurity Awareness Month theme is ‘Secure our World.’ How does this theme resonate with you, as someone working in cybersecurity? The theme ‘Secure our World’ resonates with me because I enjoy researching about cybersecurity

This post is part of a series on privacy-preserving federated learning. The series is a collaboration between NIST and the UK government’s Responsible Technology Adoption Unit (RTA), previously known as the Centre for Data Ethics and Innovation. Learn more and read all the posts published to date at NIST’s Privacy Engineering Collaboration Space or RTA’s blog . Introduction In this post, we talk with Dr. Xiaowei Huang and Dr. Yi Dong (University of Liverpool), Dr. Mat Weldon (UK Office of National Statistics (ONS)), and Sikha Pentyala (University of Washington Tacoma), who were winners in the

This blog is part of a larger NIST series during the month of October for Cybersecurity Awareness Month , called 'Staff Stories Spotlight.' Throughout the month of October this year, Q&A style blogs will be published featuring some of our unique staff members who have interesting backgrounds, stories to tell, and projects in the world of cybersecurity. This year’s Cybersecurity Awareness Month theme is ‘Secure our World.’ How does this theme resonate with you, as someone working in cybersecurity? For me, this year’s theme is a reminder of the global nature of NIST’s cybersecurity and privacy

The rapid proliferation of Artificial Intelligence (AI) promises significant value for industry, consumers, and broader society, but as with many technologies, new risks from these advancements in AI must be managed to realize it’s full potential. The NIST AI Risk Management Framework (AI RMF) was developed to manage the benefits and risks to individuals, organizations, and society associated with AI and covers a wide range of risk ranging from safety to lack of transparency and accountability. For those of us at NIST working in cybersecurity, privacy and AI, a key concern is how advancements

Human-centered cybersecurity (also known as ‘usable security’) involves the social, organizational, and technological influences on people’s understanding of and interactions with cybersecurity. By taking a human-centered cybersecurity (HCC) approach, we can both improve people's cybersecurity experiences and achieve better cybersecurity outcomes, which is so important in today’s digitally interconnected world. At NIST, we understand the value of making connections, listening, and interactivity. We also understand that researchers and practitioners want to hear directly from each other—and

In this post, we talk with Dr. Xiaowei Huang and Dr. Yi Dong (University of Liverpool), Dr. Mat Weldon ( United Kingdom (UK) Office of National Statistics (ONS)), and Dr. Michael Fenton (Trūata) who were winners in the UK-US Privacy-Enhancing Technologies ( PETs) Prize Challenges. We discuss implementation challenges of privacy-preserving federated learning (PPFL) - specifically, the areas of threat modeling and real world deployments. Threat Modeling In research on privacy-preserving federated learning (PPFL), the protections of a PPFL system are usually encoded in a threat model that defines

This post is part of a series on privacy-preserving federated learning. The series is a collaboration between NIST and the UK government’s Responsible Technology Adoption Unit (RTA), previously known as the Centre for Data Ethics and Innovation. Learn more and read all the posts published to date at NIST’s Privacy Engineering Collaboration Space or RTA’s blog . The last two posts in our series covered techniques for input privacy in privacy-preserving federated learning in the context of horizontally and vertically partitioned data. To build a complete privacy-preserving federated learning

The last few months have brought even more opportunities for NIST to engage with our international partners to enhance cybersecurity. Here are some updates on our recent international engagement: Conversations have continued with our partners throughout the world on the recent release of the Cybersecurity Framework Version 2.0 . NIST international engagement continues through our support to the Department of State and the International Trade Administration (ITA) during numerous international dialogues. Most recently, NIST participated in interagency dialogues to share information on NIST

Can you recall the last time you opened a bank account? It’s likely you walked into a local bank branch and spoke to a representative who asked for your driver’s license and social security card to verify your identity. Now imagine you want to create a bank account online. The process is likely similar—type in your social security number, take a picture of your driver’s license, and submit both to the bank via their webpage. Seems straightforward, right? Identity verification is important—it protects us from identity theft and reduces the risk of fraud and unauthorized access for organizations

I joined NIST as the first full-time manager of the NICE Framework in October 2020, just one short month before NICE published the first revision NIST Special Publication 800-181, the NICE Workforce Framework for Cybersecurity (NICE Framework). That revision – far from finalizing work – was the starting point that led us to a complete refresh of the NICE Framework components, which includes: Revised Work Role Categories and Work Roles – including one new Work Role. Eleven new Competency Areas that extend the Framework’s cybersecurity knowledge and skills. Updated Task, Knowledge, and Skill

The problem The previous post in our series discussed techniques for providing input privacy in PPFL systems where data is horizontally partitioned. This blog will focus on techniques for providing input privacy when data is vertically partitioned . As described in our third post , vertical partitioning is where the training data is divided across parties such that each party holds different columns of the data. In contrast to horizontally partitioned data, training a model on vertically partitioned data is more challenging as it is generally not possible to train separate models on different

The U.S. Small Business Administration is celebrating National Small Business Week from April 28 - May 4, 2024. This week recognizes and celebrates the small business community’s significant contributions to the nation. Organizations across the country participate by hosting in-person and virtual events, recognizing small business leaders and change-makers, and highlighting resources that help the small business community more easily and efficiently start and scale their businesses. To add to the festivities, this NIST Cybersecurity Insights blog showcases the NIST Cybersecurity Framework 2.0

We all need supplements sometimes. Whether it’s a little extra vitamin C during flu season or some vitamin D during the dark days of Winter. When used correctly, supplements help our body adjust to the changing conditions around us. Similarly, we are applying this same concept for the first time to our NIST SP 800-63B, Digital Identity Guidelines: Authentication and Lifecycle Management. Today, we published a supplement that provides interim guidance for agencies seeking to make use of ‘syncable authenticators’ ( for example, passkeys) in both enterprise-facing and public-facing use cases

In our second post we described attacks on models and the concepts of input privacy and output privacy. ln our last post, we described horizontal and vertical partitioning of data in privacy-preserving federated learning (PPFL) systems. In this post, we explore the problem of providing input privacy in PPFL systems for the horizontally-partitioned setting. Models, training, and aggregation To explore techniques for input privacy in PPFL, we first have to be more precise about the training process. In horizontally-partitioned federated learning, a common approach is to ask each participant to