GRF · AI and Digital Governance

Situational awarenessEvents, outlooks and readiness for those who decide

Cyber and public infrastructure

Public services and critical infrastructure run on digital systems that attackers target and that fail through error. Cyber governance sets security obligations, incident reporting duties and the authorities that coordinate response. This page sets out how cyber risk to public infrastructure develops and how governance responds, the records that show it, and who holds the decisions.

01Canvas

How the work runs.

Systems · around this subjectDesign, not a record

Public algorithm register

Cyber and public infrastructure · Algorithm register · Quarter 3

Two high-risk systems without assessmentGRF · AI and Digital Governance

Registered systems

Benefit fraud flaggingSocial agencyHighMissingPartial
Permit triagePlanningLimitedDoneYes
School placementEducationHighDoneYes
Chat assistantTax officeMinimalDonen/a

Oversight action

System
Benefit fraud flagging
Required
impact assessment, appeal route
Deadline
38 days
Authority
Oversight body

Complaints about automated decisions

Public algorithm register: the screen's structure, terms and states for Cyber and public infrastructure.Placeholder names and illustrative values; a design, not a record or a live system.

Fig.Public algorithm register. Design wireframe with placeholder names and illustrative values, not a record or a live system.

02The question

Cyber and public infrastructure: how the risk develops.

Governance of digital dependencies. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

Mechanism

Legacy systems persist

Public bodies run old software that is costly to replace and hard to secure. Budget cycles favour new services over patching and replacement, so known weaknesses stay.

Mechanism

Suppliers carry shared risk

Many agencies use the same software, cloud and managed service providers. A compromise of one supplier reaches all its customers at once.

Mechanism

Incidents cross sectors

Ransomware at a hospital, utility or local council disrupts physical services. Dependencies between digital and physical infrastructure turn a cyber incident into a public safety event.

Mechanism

Reporting shapes response

Mandatory incident reporting to national authorities lets them warn others and coordinate. Late or partial reporting leaves other targets exposed.

03Geography

Connected activity in East Asia.

Night lights, population density and flood water over East Asia, from NASA GIBS. Each layer carries its own date.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Connected activity, for this page

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

Connected activity, framed on East Asia. Layers as NASA publishes them, each with its own date.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA/NOAA VIIRS · NASA EONET · U.S. Geological SurveySources and licences

  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Observed (EO): NASA/NOAA VIIRS (Suomi NPP). We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
  • Live: NASA EONET Events are indicative, not authority warnings.
  • Live: U.S. Geological Survey Events are indicative, not authority warnings.
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
  • Optional layers (5 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Active fires and thermal anomalies, last day: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024

04Indicators

What is measured, and how well.

Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.

IndicatorUnitCadenceSource typeLabel
National cybersecurity strategy in forceyes or noon changeGovernment recordsPublished statistics
National computer security incident response teamyes or no, with mandateon changeFIRST and ITU recordsPublished statistics
Significant incidents reported by public bodiescount by sectorannualNational authority reportsPublished statistics
Global Cybersecurity Index tiertier, categoricalperiodicITUESTIMATED
Known exploited vulnerabilities remediated within deadlineshareperiodicAgency compliance reportsREPORTED
Public service downtime from cyber incidentshoursper incidentIncident reportsREPORTED
05Decision model

Where coupling turns damage into an outage.

How spare capacity and dependencies between sectors decide whether local damage stays local, the levers resilience regulation and investment can pull. Teaching model with stated illustrative values, not a prediction. The map on this page shows East Asia; the model itself is not tied to a place.

Controls

Assets per layer
18
Hazard footprint
8 % of area
Assets that depend on another layer
60 %
Spare capacity (tolerance)
30 %

Readouts

Assets hit by the hazard
7 %
Assets still working
20 %
Amplification of the initial damage
10.8 times
Steps to settle
4
Numbers, methods and sources
StepData centres working (%)Networks working (%)Power working (%)
08989100
1567294
2503328
3333311
422336

Methods

  1. Interdependent networks Buldyrev and others (2010), Catastrophic cascade of failures in interdependent networks, Nature 464
  2. Overload cascades Motter and Lai (2002), Physical Review E 66
  3. Betweenness load Brandes (2001), Journal of Mathematical Sociology 25
  4. Multilayer networks Kivela and others (2014), Journal of Complex Networks 2
  5. Infrastructure interdependencies Rinaldi, Peerenboom and Kelly (2001), IEEE Control Systems 21(6)
  6. Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualizing uncertainty about the future, Science 333
  7. One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley

Data

The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page's map can draw:

  • Major roads Natural Earth
  • Railways Natural Earth
  • Seaports Natural Earth
  • Airports Natural Earth
  • Urban extents Natural Earth
  • Night lights tonight, outages (VIIRS Day/Night Band) NASA/NOAA VIIRS (Suomi NPP) · register nasa.gibs.context-live-layers
  • Natural events (NASA EONET) NASA EONET · register nasa.eonet.events
06Canvas

From sources to decisions.

The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.

Pipeline canvas · Cyber and public infrastructure as a run graphDesign, not a record
Cyber and public infrastructure: incident response across CSF 2.0 functionsAn adverse event is detected and triaged; response analyses, contains and communicates; recovery restores services from clean backups; improvement and governance close the loop with lessons and reporting. Design of the process, not a record of a run.

Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.

07Implementation

From mandate to evaluation, by pillar.

The steps an instrument takes from mandate to evaluation, each in the lane of the pillar that runs it and the authority's decisions in their own lane; play it step by step. Teaching model with stated illustrative values, not a prediction. The map on this page shows East Asia; the model itself is not tied to a place.

08Sources

Where the evidence comes from.

Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.

SourceWhat it givesLicence class
ITU Global Cybersecurity IndexCountry commitments on legal, technical, organizational, capacity and cooperation measuresFree to read, ITU terms
ENISA Threat Landscape and NIS incident reportsThreats and incidents across EU sectorsFree, ENISA terms
CISA Known Exploited Vulnerabilities catalogVulnerabilities known to be exploited, with remediation deadlines for US federal agenciesPublic domain
National cyber security centre annual reviewsIncidents handled and threat assessmentsPublic records, terms per centre
FIRST member directoryIncident response teams and their constituenciesFree to read, FIRST terms
09Twin and cascade simulator

Exercise a cascade in cyber and public infrastructure with the people who decide.

Assembled from the Nexus Standards area profile Cyber and digital risk standards: the hazards it names, the systems and communities that carry the loss, the controls and institutions that dampen it and the data that observe it. Pick an initiating event and step through the cascade to see where mandates meet and which decisions fall to whom. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise for dialogue, not a forecast, an assessment or a position.

Hazards

  • Dam failure
  • River flood (set off downstream)
  • Flash flood (set off downstream)
  • Mass displacement (set off downstream)
  • Widespread power outage (set off downstream)
  • Water supply shortfall (set off downstream)

Controls

  • NS-0 Constitution and principles
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-10 Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NS-12 Software, model and AI/ML artifacts (supply chain, model cards, dataset sheets)
  • NRS-H94 Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)
  • NRS-X6 Cyber and digital security risk
  • NRS-H51 Hazard family: Malicious compromise (NHS-1 cyber.intrusion)
  • NRS-T8 Software and supply-chain integrity risk
  • NRS-H93 Hazard family: Identity, trust and cryptographic failure (NHS-1 cyber.identity)
  • NRS-H54 Hazard family: Signal and platform disruption (NHS-1 cyber.platform)

Observation

  • National Vulnerability Database (CVE enrichment API) (listed for reference)
  • Known Exploited Vulnerabilities catalogue (listed for reference)
  • OSV open source vulnerability database (listed for reference)
  • MITRE ATT&CK knowledge base (STIX 2.1) (listed for reference)
  • Proportion of population covered by a mobile network, by technology
  • Fixed Internet broadband subscriptions per 100 inhabitants

Example geography

  • North America: 243 H3 hexagons at resolution 2
  • Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
  • Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
  • Rain rate, last half hour (IMERG), NASA GIBS
  • Surface soil moisture (SMAP), NASA GIBS
10Decisions

Who decides, and what the evidence serves.

AI and Digital Governance prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

Who decidesThe questionEvidence this page serves
National cybersecurity authoritiesWhich obligations apply and how incidents are coordinatedComparative regimes and incident data
Public body leadershipHow much to invest in security and legacy replacementThreat data and comparable practice
LegislaturesWhich sectors fall under cyber obligations and reporting dutiesComparative laws and incident evidence
Procurement authoritiesWhat security requirements suppliers must meetSupply chain incident evidence and standards

Outputs this topic produces

  • Comparative notes on cyber obligations for public bodies
  • Guide to incident reporting regimes and timelines
  • Dialogue briefs on shared supplier risk in public services
  • Questions for public boards on cyber oversight
11Instruments and commitments

How cyber and public infrastructure is governed: instruments, mandates and commitments.

The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.

Policy instrument matrix

The kinds of instrument available on cyber and public infrastructure, by level of government and cooperation.

Instrument typeLocalNationalRegionalGlobal
RegulatoryZoning, building codesLaws, standards, licensingHarmonised rulesConventions and treaties
EconomicLocal levies, grantsBudget lines, taxes, insurance schemesRisk pools, regional fundsFinancing mechanisms
InformationLocal warningsDisclosure, early warning, statisticsData sharing arrangementsGlobal monitoring and reporting
InstitutionalLocal committeesLead agencies, coordination councilsRegional bodies and secretariatsMultilateral mandates
CooperativeCommunity agreementsPartnership compactsMemoranda and joint programmesAgreements and joint commitments
A typology after the OECD Recommendation on the Governance of Critical Risks; examples of instrument types, not an inventory of any country's measures.
Sendai Framework for Disaster Risk Reduction · UNDRRParis Agreement · UNFCCC2030 Agenda and the Sustainable Development Goals · United NationsInternational Health Regulations · WHO
12Core questions

What institutions ask about digital dependencies.

  • Which public services would stop if a given system, provider or network failed?
  • Who is responsible for securing each dependency, and are those responsibilities clear in contracts?
  • How are incidents reported, coordinated and communicated to the public?
  • How exposed is the public sector to a single provider or software component?
13Mechanisms

How cyber risk reaches public services.

Ransomware attacks on hospitals, local governments and schools have shown how quickly encrypted systems can halt services, with patients diverted and payments delayed. Supply chain compromises, in which attackers enter through a trusted software update or provider, can reach many organizations at once. Faulty updates from a single vendor have also disrupted services widely without any attack at all.

Public bodies often have older systems, limited security staff and complex procurement, which makes them attractive targets. Responsibility is fragmented between the agency, its suppliers and national cyber authorities. Concentration on a few cloud and software providers creates efficiency and security benefits but also shared points of failure.

Why now: cyber incidents now halt hospitals, ports and payments, and the UN process on security in the use of information technologies agreed in 2025 to move to a permanent mechanism. The platform is designed to convene public infrastructure owners on decision rights during an incident and exercise them without touching live systems.

14Methods and limits

Instruments of governance.

  1. 01

    Dependency mapping

    Identifying which services depend on which systems and providers. Limits: hidden sub-dependencies.

  2. 02

    Baseline security requirements

    Minimum controls for public bodies and suppliers. Limits: compliance does not ensure security.

  3. 03

    Incident reporting and coordination

    Mandatory reporting and national coordination. Limits: under-reporting and slow information sharing.

  4. 04

    Exercises

    Cross-agency cyber exercises. Limits: participants know it is an exercise.

15Methods

How it is studied, and what the methods cannot say.

  1. Policy, institutional and decision scienceComparing AI regimes · Value chain accountability mapping · Forum and mandate mappingApplied here
  2. Digital identity and public digital systemsAssurance levels for public services · Minimal disclosure · Exclusion analysisApplied here
  3. Artificial intelligence and machine learningHow models fail in deployment · Reading model documentation · Agent architectures explainedApplied here
16Questions

Questions and answers.

What is a CSIRT?
A computer security incident response team that receives, analyses and coordinates responses to cyber incidents for a defined constituency, such as a country or sector.
What does NIS2 require?
Essential and important entities in the EU must manage cybersecurity risks, report significant incidents within set deadlines and hold management bodies accountable.
Why are public bodies frequent targets?
They hold valuable data, run essential services, often use legacy systems and may pay to restore services, which attracts ransomware groups.
Should I report a cyber incident to the platform?
No. Report incidents to your national cyber authority and follow your organization's incident procedures.
Is moving to cloud safer for public bodies?
It can improve security for many organizations, but it also creates dependence on providers. The trade-off should be assessed for each service.
Does the platform publish vulnerability information?
No. It discusses governance patterns, not specific vulnerabilities.
Why is responsibility for public cyber security fragmented?
Because agencies, suppliers and national authorities each hold part of it. Clear contracts and coordination arrangements reduce the gaps.
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