ESA carries trusted test data from factory to orbit

Keysight Technologies will lead a three-year European Space Agency programme developing a blockchain-enabled trust and anomaly-detection framework for 5G non-terrestrial networks, with Sateliot supporting technical development and satellite mission integration.

The project forms part of ESA’s Space for 5G/6G and Sustainable Connectivity activity under the Advanced Research in Telecommunications Systems programme. Blockchain, artificial intelligence, machine learning, secure telemetry, and digital calibration certificates will be examined across a lifecycle extending from satellite manufacture and ground test to in-orbit operation and service delivery.

Laboratory research and prototyping will precede a full in-orbit demonstration. The partners will test whether network data, calibration records, commands, and operational events can be made sufficiently traceable and verifiable to support secure, increasingly autonomous management of hybrid satellite and terrestrial infrastructure.

Non-terrestrial 5G connects spacecraft, gateways, mobile-network equipment, user terminals, cloud platforms, and terrestrial radio systems. The resulting assurance boundary is considerably larger than that of a standalone satellite link.

A fault or security event could originate in flight hardware, ground software, calibration data, a network update, a compromised terminal, an altered command, or deliberate spoofing. Diagnosing the source requires trustworthy records spanning organisations and technical domains.

Sateliot’s low-Earth-orbit network uses 5G narrowband Internet of Things standards to connect devices through existing mobile-network arrangements. Its involvement gives the programme an operational satellite environment in which to examine handovers, telemetry, network management, and interaction with terrestrial systems.

Factory evidence follows the spacecraft into service

Digital calibration certificates provide one of the programme’s clearest links to manufacturing. Satellite instruments, radio-frequency equipment, test systems, and ground infrastructure are calibrated against defined standards during production and maintenance.

Those records establish what was tested, when the work occurred, which equipment was used, and what measurement uncertainty applied. They are normally treated as quality documents, but autonomous network management may also need them during operation.

An anomaly-detection system interpreting a change in signal quality could require confirmation that the relevant sensor, instrument, or ground system remained within calibration. It may also need to know whether a software update, configuration change, or maintenance event occurred shortly before the behaviour changed.

A blockchain-based framework could provide a tamper-evident chain linking calibration, manufacturing, software, and operational events. Such a system would not prove that every measurement was accurate, but it could reveal altered records, missing provenance, or unauthorised changes.

Governance will be as important as cryptography. The architecture must define who can add records, how mistakes are corrected, which participants can see sensitive data, and how access changes when suppliers or operators leave the programme.

Distributed ledgers also carry processing, storage, bandwidth, and latency overhead. Space and tactical networks cannot replicate unlimited volumes of data, so the practical design may store hashes, signatures, permissions, or selected events while larger technical records remain in controlled repositories.

AI and machine learning will support anomaly detection across the network. Effective models need training data covering normal changes in orbit, traffic, weather, handovers, equipment ageing, and terrestrial-network behaviour.

Without enough context, software may treat normal variation as an attack or fail to identify carefully shaped interference. False alarms would burden operators, while missed anomalies could leave spoofing or tampering undetected.

The programme’s defence relevance rests on resilience across the supply chain. Military and national-security satellite services must account for jamming, spoofing, cyber intrusion, compromised components, altered software, and misleading telemetry as related risks rather than isolated events.

Trust cannot begin after launch. It has to include the equipment, calibration, test data, software, and records created during manufacture.

Hardware-based protection is already being introduced into European satellite links, including Xiphera’s work on cybersecurity technology for ESA communications. The Keysight and Sateliot programme addresses the accompanying data and assurance layer across several stages of operation.

Keysight’s test-and-measurement role places production evidence near the centre of the architecture. Test equipment is often trusted implicitly, even though expired calibration, corrupted configuration, insecure result handling, or altered software can weaken the evidence used to release hardware.

Binding measurements to verifiable records could strengthen factory acceptance, in-orbit troubleshooting, and later software upgrades. Engineers investigating anomalous behaviour would have a more reliable history of the equipment and data behind it.

The in-orbit demonstration will test whether that approach survives operational complexity. Laboratory systems can be isolated and reset, whereas satellites encounter intermittent connections, handovers, software updates, constrained bandwidth, and normal performance variation.

Interoperability will determine whether the framework can extend beyond one constellation. NTN services involve spacecraft manufacturers, payload suppliers, operators, mobile networks, terminal providers, cloud platforms, and test-equipment companies.

A system dependent on proprietary formats or a single ledger implementation would struggle to cross that market. Shared data models, controlled interfaces, and clear ownership of records will be required for broader adoption.

ESA’s three-year structure gives the partners time to move beyond a laboratory proof and accumulate operational evidence. The useful result will be a traceable chain showing where data originated, which hardware and software produced it, how integrity was checked, and what an automated system may do when trust deteriorates.