The authors discuss the need and potential for normative constraints on cyber aggression. They describe how norms tend to arise, review the history of governmental and private initiatives on cyber norms, and outline principles governing U.S. policy on the issue. The authors propose a bottom-up, ?outside-in? agenda for the United States to encourage the development of norms to limit the most damaging forms of cyber aggression.

Competition and Restraint in Cyberspace: The Role of International Norms in Promoting U.S. Cybersecurity

Computers & Technology

Mazarr, Michael J.

Frederick, Bryan

Ellinger, Emily

Boudreaux, Benjamin

Networking & Cloud Computing

RAND Corporation

The authors of this report developed and tested the potential for new interviewing methods, including the use of machine learning (ML), to detect speech patterns that reflect attempts at deception or truthfulness during simulated background investigation interviews. They found that ML models are promising tools that have the capacity to augment existing security clearance background investigation processes.

Looking for Lies: An Exploratory Analysis for Automated Detection of Deception

Johnson, Christian

Posard, Marek N.

Reininger, Hilary

Melin, Julia L.

Computer Science

The return of great-power competition has highlighted the risks of conflict with nuclear-armed great powers. Such a conflict would entail escalation risks that the United States has not seriously considered since the Cold War. Using three historical case studies, the authors examine decisionmakers' ability to identify adversary thresholds and to apply this information to control escalation during militarized crises between nuclear-armed states.

Managing Escalation: Lessons and Challenges from Three Historical Crises Between Nuclear-Armed Powers

History

Heim, Jacob L.

Beauchamp-Mustafaga, Nathan

Evans, Alexandra T.

Burdette, Zachary

Asia

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Books by Ellinger, Emily