Post-quantum cryptographic assemblages and the governance of the quantum threat
Bibliographic record
Abstract
Abstract Threats against security in the Internet often have a wide range and can have serious impacts within society. Large quantum computers will be able to break the cryptographic algorithms used to ensure security today, which is known as the quantum threat. Quantum threats are multi-faceted and very complex cybersecurity issues. We use assemblage theory to explore the complexities associated with these threats, including how they are understood within policy and strategy. It is in this way that we explore how the governance of the quantum threat is made visible. Generally, the private and academic sectors have been a primary driver in this field, but other actors (especially states) have begun to grapple with the threat and have begun to understand the relation to defence challenges, and pathways to cooperation in order to prepare against the threat. This may pose challenges for traditional avenues of defence cooperation as states attempt to understand and manage the associated technologies and perceived threats. We examine how traditionally cooperating allies attempt to govern the quantum threat by focusing on Australia, Canada, European Union, New Zealand, UK, and USA. We explore the linkages within post-quantum cryptographic assemblages and identify several governmental interventions as attempts to understand and manage the threat and associated technologies. In examining over 40 policy and strategy-related documents between traditionally defence cooperating allies, we identify six main linkages: Infrastructure, Standardization, Education, Partnerships, Economy, and Defence. These linkages highlight the governmental interventions to govern through standardization and regulation as a way to define the contours of the quantum threat.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.033 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".