CSET's Ali Crawford and Jessica Ji submitted this comment to the Office of the National Cyber Director in response to a request for information on a national strategy for a cyber workforce, training, and education.

CSET's Catherine Aiken testified before the National Artificial Intelligence Advisory Committee on measuring progress in U.S. AI research and development.

China is rapidly building cyber ranges that allow cybersecurity teams to test new tools, practice attack and defense, and evaluate the cybersecurity of a particular product or service. The presence of these facilities suggests a concerted effort on the part of the Chinese government, in partnership with industry and academia, to advance technological research and upskill its cybersecurity workforce—more evidence that China has entered near-peer status with the United States in the cyber domain.

Funding and priorities for technology development today determine the terrain for digital battles tomorrow, and they provide the arsenals for both attackers and defenders. Unfortunately, researchers and strategists disagree on which technologies will ultimately be most beneficial and which cause more harm than good. This report provides three examples showing that, while the future of technology is impossible to predict with certainty, there is enough empirical data and mathematical theory to have these debates with more rigor.

In the current cyber-threat environment, a well-educated workforce is critical to U.S. national security. Today, however, nearly six hundred thousand cybersecurity positions remain unfilled across the public and private sectors. This report explores high school cybersecurity competitions as a potential avenue for increasing the domestic cyber talent pipeline. The authors examine the competitions, their reach, and their impact on students’ educational and professional development.

We aim to demonstrate the value of mathematical models for policy debates about technological progress in cybersecurity by considering phishing, vulnerability discovery, and the dynamics between patching and exploitation. We then adjust the inputs to those mathematical models to match some possible advances in their underlying technology.

Adversarial patches are images designed to fool otherwise well-performing neural network-based computer vision models. Although these attacks were initially conceived of and studied digitally, in that the raw pixel values of the image were perturbed, recent work has demonstrated that these attacks can successfully transfer to the physical world. This can be accomplished by printing out the patch and adding it into scenes of newly captured images or video footage.

CSET Senior Fellow Andrew Lohn testified before the House of Representatives Homeland Security Subcommittee on Cybersecurity, Infrastructure Protection, and Innovation at a hearing on "Securing the Future: Harnessing the Potential of Emerging Technologies While Mitigating Security Risks." Lohn discussed the application of AI systems in cybersecurity and AI’s vulnerabilities.

CSET Senior Fellow Andrew Lohn testified before the House of Representatives Science, Space and Technology Subcommittee on Investigations and Oversight and Subcommittee on Research and Technology at a hearing on "Securing the Digital Commons: Open-Source Software Cybersecurity." Lohn discussed how the United States can maximize sharing within the artificial intelligence community while reducing risks to the AI supply chain.

CSET Senior Fellow Andrew Lohn testified before the U.S. Senate Armed Services Subcommittee on Cybersecurity hearing on artificial intelligence applications to operations in cyberspace. Lohn discussed AI's capabilities and vulnerabilities in cyber defenses and offenses.