Advanced Industry and Robotics
The Global Centre for Risk and Innovation (GCRI)
GCRI · Advanced Industry and Robotics
Spatial intelligenceObservations, models and their uncertainty in one view
Factories and process plants depend on operational technology that was designed for reliability, not security, and is now connected to business networks and suppliers. Ransomware and targeted attacks can stop production, damage equipment or create safety hazards. This page sets out how cyber threats affect industrial operations, how resilience is built and measured, and what evidence serves the operators and regulators involved.
OT/ICS and connected factories. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Remote access, cloud services and integration with suppliers connect control systems to networks attackers can reach.
Ransomware on business systems often halts production because scheduling, logistics and quality systems are unavailable, even if controls are untouched.
Attacks on safety instrumented systems or controls could create hazardous conditions, so security must be part of safety engineering.
Plants that can run or shut down safely without their digital systems recover faster and more safely.
Night lights, population density and true-colour imagery over Germany, from NASA GIBS. Each layer carries its own date.
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Layers 3
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NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
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Connected activity, framed on Germany. 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.
Layers and dates
Findings are designed for the Global Sector Risk and Resilience series. IEC 62443 sets the security framework; the page publishes no vulnerability detail.
A hazard footprint takes out co-located assets in every layer; fragmentation, dependency between layers and overload of the survivors then spread the failure. The 3D view separates the layers by depth. Teaching model with stated illustrative values, not a prediction. The map on this page shows Germany; the model itself is not tied to a place.
Controls
Readouts
| Step | Data centres working (%) | Networks working (%) | Power working (%) |
|---|---|---|---|
| 0 | 94 | 94 | 67 |
| 1 | 94 | 56 | 50 |
| 2 | 83 | 22 | 22 |
| 3 | 44 | 22 | 22 |
| 4 | 44 | 17 | 17 |
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:
Across the six pillars, led by Nexus Consortium
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.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Industrial cyber incidents reported | count by sector | annual | Agency incident reporting | Published statistics |
| Production days lost to cyber incidents | days | per incident | Incident records | OBSERVED |
| ICS vulnerability advisories | count | monthly | National advisories | Published statistics |
| Sites with IT and OT segmentation | percent of sites | per assessment | Operator assessments | DECLARED |
| Sites with tested manual fallback | percent of sites | per assessment | Exercise records | REPORTED |
| Remote access connections to OT | count | per assessment | Network inventories | OBSERVED |
Assembled from the Nexus Standards area profile Cyber and digital resilience law alignment: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification.
Hazards
Systems and couplings
Controls
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-9 Contextual UNIs (deployments, instances, programme instances)NRS-X6 Cyber and digital security riskNRS-H93 Hazard family: Identity, trust and cryptographic failure (NHS-1 cyber.identity)NRS-K31 Domain pack profile: Cyber national resilience (DOMAIN-031)NRS-H54 Hazard family: Signal and platform disruption (NHS-1 cyber.platform)NRS-H86 Hazard family: Telecom and data-centre failure (NHS-1 infra.digital)NRS-H94 Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)Observation
Example geography
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.
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.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
The couplings between the systems in industrial cyber resilience: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| CISA industrial control systems advisories | Vulnerabilities and mitigations in control products | Public domain, US government |
| ENISA reports on industrial and OT security | Threat and good practice analysis | Public, ENISA terms |
| IEC 62443 series | Industrial automation security requirements | Licensed standards, purchase required |
| Joint agency advisories on threats to operational technology | Actor behaviour and mitigations | Public, terms per agency |
| Published incident reviews from manufacturers | Effects and recovery after incidents | Public records, terms per publisher |
Advanced Industry and Robotics prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Plant operators | How to segment, monitor and keep manual fallback | Security reviews; dependency maps |
| Industrial and safety regulators | What OT security to require | Incident and advisory evidence |
| Suppliers and integrators | How to secure remote access and products | Remote access evidence |
Pathways through business networks, remote access, suppliers and removable media.
Production loss, equipment damage, safety system interference and environmental release.
Long equipment lifetimes, real-time constraints and safety priorities that limit patching and monitoring.
Manual operation, segmentation, backups and restoration of trusted configurations.
Industrial control systems were designed for reliability, not security. Many run legacy software that cannot easily be updated, and some protocols lack authentication. Connectivity for efficiency and remote support has widened the attack surface.
Ransomware on business systems often forces plants to stop production even when control systems are untouched, because scheduling, logistics or safety documentation depend on IT. This coupling is a frequent cause of industrial disruption.
Targeted attacks on control and safety systems are rarer but serious, because they can cause physical damage. Defence in depth, network segmentation and independent safety systems limit consequences.
Supply chains extend risk. Compromised vendor software, integrators and shared platforms can affect many sites at once.
Resilience depends on people as much as technology. Plants that can run key processes manually, keep trusted offline backups and rehearse recovery with operators and engineers together restore operations faster than those relying on technical controls alone.
| Method or data | What it shows | Its limit |
|---|---|---|
| Network architecture review | Segmentation and access paths | Documentation often lags reality |
| Consequence-driven analysis | Worst credible physical outcomes | Requires joint safety and security expertise |
| Incident reports | Patterns in industrial cyber events | Under-reporting and confidentiality |
| Exercises | Recovery capability | Exercises simplify real attacks |
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Nexus Reports is the Consortium's quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
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