219 citations · 263 across the 14 of their papers we have counts for
14 papers
Defending Against Intelligent Attackers at Large Scales
Andrew J. Lohn
We investigate the scale of attack and defense mathematically in the context of AI's possible effect on cybersecurity. For a given target today, highly scaled cyber attacks such as…
The Impact of AI on the Cyber Offense-Defense Balance and the Character of Cyber Conflict
Andrew J. Lohn
Unlike other domains of conflict, and unlike other fields with high anticipated risk from AI, the cyber domain is intrinsically digital with a tight feedback loop between AI traini…
Confidence-Building Measures for Artificial Intelligence: Workshop Proceedings
Sarah Shoker, Andrew Reddie, Sarah Barrington +20
Foundation models could eventually introduce several pathways for undermining state security: accidents, inadvertent escalation, unintentional conflict, the proliferation of weapon…
Adversarial Machine Learning and Cybersecurity: Risks, Challenges, and Legal Implications
Micah Musser, Andrew Lohn, James X. Dempsey +14
In July 2022, the Center for Security and Emerging Technology (CSET) at Georgetown University and the Program on Geopolitics, Technology, and Governance at the Stanford Cyber Polic…
Will AI Make Cyber Swords or Shields: A few mathematical models of technological progress
Andrew J Lohn, Krystal Alex Jackson
We aim to demonstrate the value of mathematical models for policy debates about technological progress in cybersecurity by considering phishing, vulnerability discovery, and the dy…
Empirical Evaluation of Physical Adversarial Patch Attacks Against Overhead Object Detection Models
Gavin S. Hartnett, Li Ang Zhang, Caolionn O'Connell +2
Adversarial patches are images designed to fool otherwise well-performing neural network-based computer vision models. Although these attacks were initially conceived of and studie…