Research Library

CyberCAN: Cybersecurity for Cities and Nonprofits

By: Sarah Powazek, Shannon Pierson

A new CLTC report provides guidance to help government leaders in San Francisco and other cities more effectively support the digital security of local nonprofits. The report, “CyberCAN:…

Resistance to Text-to-Image Generators in Creator Communities

Text-to-image generators like DALL-E have sparked controversy among artistic creators, who are concerned about how generative artificial intelligence (Gen AI) models have been trained with copyright-protected materials. A…

Cyber Resilience and Social Equity: Twin Pillars of a Sustainable Energy Future

By: Emma Stewart, Remy Stolworthy, Virginia Wright

A report published by the Center for Long-Term Cybersecurity, Cyber Resilience and Social Equity: Twin Pillars of a Sustainable Energy Future, examines the importance of cybersecurity in ensuring equitable access to energy. In an era of worsening cybersecurity threats, the paper advocates for “sustainable energy delivery systems that ensure robust defenses without compromising the goals of reducing energy poverty and ensuring energy security.”

A Swarm Intelligence Approach to Prioritizing the CIS Controls V8.0 Implementation

By: Hayat Abdulla Asad Cue, Thirimachos Bourlai, Mark Lupo

Authored by researchers affiliated with CyberArch, a cybersecurity clinic at the University of Georgia’s Carl Vinson Institute of Government (CVIOG), this paper introduces a novel approach for ranking actions outlined in the Center for Internet Security (CIS) framework, a prioritized set of safeguards to help organizations mitigate common cyber attacks.

Improving the Explainability of Artificial Intelligence: The Promises and Limitations of Counterfactual Explanations

By: Alexander Asemota, Improving the Explainability of Artificial Intelligence: The Promises and Limitations of Counterfactual Explanations

A new white paper from the Center for Long-Term Cybersecurity explores diverse approach to explainable artificial intelligence (xAI), focusing on counterfactual explanations, or CTEs. The paper, “Improving the Explainability of Artificial Intelligence: The Promises and Limitations of Counterfactual Explanations,” was authored by Alexander Asemota, a 2023-2024 AI Policy Hub Fellow.

Benchmark Early and Red Team Often: A Framework for Assessing and Managing Dual-Use Hazards of AI Foundation Models

By: Anthony Barrett, Krystal Jackson, Jessica Newman, Nada Madkour, Evan R. Murphy, Benchmark Early and Red Team Often: A Framework for Assessing and Managing Dual-Use Hazards of AI Foundation Models

Authored by Anthony M. Barrett, Krystal Jackson, Evan R. Murphy, Nada Madkour, and Jessica Newman, this report assesses two methods for evaluating the “dual-use” hazards of AI foundation models, which include large language models (LLMs) such as GPT-4, Gemini, Claude 3, Llama 3, and other general purpose AI systems.

The Transaction Costs of Municipal Cyber Risk Management

By: Rowland Herbert-Faulkner

This white paper, The Transaction Costs of Municipal Cyber Risk Management, brings to light the transaction costs associated with municipal cyber risk management, including the costs of searching for information, coordination between parties, drawing up and enforcing contracts, negotiation, inventory and monitoring, and compliance and enforcement. The paper was authored by by Rowland Herbert-Faulkner, a PhD Candidate in the Department of City and Regional Planning at UC Berkeley whose dissertation research focuses on technology governance at the municipal and regional scales.

Representing Privacy Legislation as Business Risks

By: Andrew Chong, Richmond Wong

For this CLTC white paper, researchers Richmond Wong and Andrew Chong used Form 10-K documents — annual regulatory reports for investors that publicly traded companies must file with the U.S. Securities and Exchange Commission (SEC) — to analyze how nine major technology companies assess and integrate the business risks of privacy regulation like the EU’s General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the California Privacy Rights Act (CPRA).

Cybersecurity Futures 2030: New Foundations

To better understand how diverse forces are shaping the future of cybersecurity for governments and organizations, the Center for Long-Term Cybersecurity (CLTC), the World Economic Forum Centre for Cybersecurity, and CNA’s Institute for Public Research collaborated on “Cybersecurity Futures 2030: New Foundations,” a foresight-focused research initiative that aims to inform cybersecurity strategic plans around the globe.

AI Risk-Management Standards Profile for General-Purpose AI Systems (GPAIS) and Foundation Models

By: Anthony Barrett, Jessica Newman, Brandie Nonnecke

Increasingly general-purpose AI systems, such as BERT, CLIP, GPT-4, DALL-E 2, and PaLM, can provide many beneficial capabilities, but they also introduce risks of adverse events with societal-scale consequences. This document provides risk-management practices or controls for identifying, analyzing, and mitigating risks of such AI systems. The document is intended primarily for developers of these AI systems; others that can benefit from this guidance include downstream developers of end-use applications that build on a general-purpose AI system platform. This document facilitates conformity with leading AI risk management standards and frameworks, adapting and building on the generic voluntary guidance in the NIST AI RMF and ISO/IEC 23894 AI risk management standard, with a focus on the unique issues faced by developers of increasingly general-purpose AI systems.