QUECWA FACT FILE · Original structured learning resource
Expert: Research, assurance and continuous crypto-agility
OBA outcome — Challenge: Critically appraise new PQC claims, evaluate implementation evidence and update recommendations as standards and threats evolve.
← Full pathwayResearch, assurance and continuous crypto-agility
Expertise is maintained
Advanced and Expert may require similar technical knowledge. Expert practice adds systematic monitoring of new standards, cryptanalysis, side-channel findings, implementation flaws and deployment evidence.
AI and cryptanalysis
Machine learning may help analyse side-channel leakage, automate discovery and test implementations. Claims that AI can infer properly generated PQC private keys directly from public signatures need reproducible evidence and must not be presented as established capability.
Crypto-agility
Architectures should support controlled algorithm changes through abstraction, policy, inventories, key management, testing and governance. A future migration may still require protocol, hardware or software changes; crypto-agility reduces friction rather than promising zero effort.
Continual judgement
An expert assesses source quality, threat model, reproducibility, scope and practical impact, then records whether an advisory changes the organisation's risk posture or migration plan.
Founder video: Research, assurance and continuous crypto-agility
This is a timed production outline, not a recorded video. The finished video will be no longer than five minutes.
- 0:00–1:00 — Introduce an emerging claim and its evidence.
- 1:00–2:15 — Distinguish cryptanalysis from side-channel exploitation.
- 2:15–3:30 — Review crypto-agility controls.
- 3:30–4:40 — Demonstrate an expert change-impact decision.
Three things worth remembering
- Expertise is maintained: Advanced and Expert may require similar technical knowledge. Expert practice adds systematic monitoring of new standards, cryptanalysis, side-cha
- AI and cryptanalysis: Machine learning may help analyse side-channel leakage, automate discovery and test implementations. Claims that AI can infer properly generated
- Crypto-agility: Architectures should support controlled algorithm changes through abstraction, policy, inventories, key management, testing and governance. A fut
Explain, don't guess
Show what you can do
Critically review a hypothetical AI-assisted PQC attack claim in one page. State evidence needed, alternative explanations and what would change your advice.
Show evaluation criteria
A good response differentiates hypothesis from demonstration, identifies scope and uncertainties, and gives a conditional recommendation.
Self-assessment only. A score or completion here is not a professional certification.
Authoritative references: ASD / ACSC (including the ISM and PQC transition guidance) · NIST PQC project · FIPS 203 · FIPS 204 · FIPS 205. Check current versions and applicability before acting.
Source foundation: founder-authored educational course material, adapted and independently revised for QUECWA. Content is educational and subject to continuing technical review.