The National Security Agency (NSA) has awarded the 12th Annual Best Scientific Cybersecurity Paper Competition to “Decoding Trust: Comprehensive Assessment of Trustworthiness in GPT Models.” The winning paper, authored by 19 researchers including Professors Dawn Song (UC Berkeley), Bo Li (UIUC), and Sanmi Koyejo (Stanford), proposes a groundbreaking evaluation framework for assessing the trustworthiness of large language models (LLMs) such as GPTs.

The National Security Agency has published their 2023 Cybersecurity Year in Review!

In an effort to be more transparent, the National Security Agency publishes an annual year in review sharing information regarding cybersecurity efforts that better equipped U.S. defenses against high priority cyber threats. NSA’s efforts to help secure the nation’s most sensitive systems also help your cybersecurity because NSA cascades these solutions through public guidance and engages with key technology providers to help them bolster the security of their products and services.

Vanderbilt University has announced that OpenAI CEO Sam Altman will deliver the opening keynote at the upcoming Summit on Modern Conflict and Emerging Threats, set to take place on April 17-18, 2025. The summit will bring together leading experts from government, academia, and industry to discuss the evolving landscape of national security in the age of artificial intelligence, cybersecurity, and geopolitical instability.

The National Academies is hosting a Workshop on Technology for Data Stewardship on February 29, 2025, bringing together experts from academia, industry, and government to explore cutting-edge solutions for managing and protecting data. The event will focus on advancements in data stewardship, including secure storage, access control, and ethical considerations in data sharing. Participants will discuss emerging technologies, best practices, and policy implications to ensure responsible data management across sectors.

The Center for Cyber-Social Dynamics is delighted to invite submissions for the Workshop on Advancing Fairness in Machine Learning, a multidisciplinary platform aimed at fostering dialogue between researchers, practitioners, and policymakers.