1. Definition and scope
Compute integrity is not a single product and not a vendor claim. It is a category that becomes meaningful when integrity evidence can be expressed, verified, and referenced in governance and procurement language.
In plain terms, compute integrity answers a simple question: can the system prove it is running what it should be running, on a platform whose trust anchors are understood, and that it has not been silently altered.
2. Where the category shows up (descriptive reality)
- Measured boot and chain-of-trust approaches that record integrity measurements over startup stages.
- Hardware-rooted trust primitives used as foundations (for example TPM-based measurement and related approaches), without reducing the category to one technology.
- Remote attestation concepts where a verifier validates claims about the state of a device or workload.
- Integrity verification expectations in critical deployments where assurance evidence is required.
3. Why it matters now
Three converging forces move compute integrity from engineering concerns to board and procurement language. First, resilience expectations shift the question from “is it secure” to “can it prove, continuously and verifiably, that it is not compromised.” Second, European cyber and product-security trajectories increasingly reward measurable and attestable assurance properties over time. Third, AI deployment at scale expands the trust problem: even if an output is signed or logged, stakeholders still ask whether the environment that produced it was trustworthy.
4. A neutral framework (five dimensions)
A practical way to keep the category legible, without turning it into a product pitch, is to structure it as a simple five-dimension framework. These dimensions are descriptive lenses. They do not imply a certification.
- Integrity evidence: what observations or measurements can be produced as evidence of state.
- Attestation and verification: how evidence is conveyed and how a relying party validates it at a high level.
- Policy and relying parties: who relies on integrity claims, and what policies determine acceptance.
- Lifecycle coverage: how integrity concerns differ across boot, update, runtime, and recovery.
- Governance language: how integrity requirements are expressed in risk, assurance, and procurement narratives.
5. Why it will matter for AI systems
AI trust debates often focus on outputs, logs, and provenance. Compute integrity is the foundation beneath those layers. If an organisation requires trustworthy automated decisions, it eventually needs credible assumptions about the execution environment that produced those decisions. Integrity evidence makes higher-level guarantees more meaningful, without claiming to “solve” AI risk.
6. Guardrails for safe stewardship
- Non-affiliation: no suggestion of official status, endorsement, partnership, or certification by any authority or standards body.
- No services: no offer of pentesting, audit, certification, compliance assessment, or security operations.
- No guarantees: no “compliance assured,” no “certified,” no “approved.”
- Neutral design: no institutional mimicry, no third-party logos, no confusing visual identity.
- Trademark respect: all trademarks belong to their respective owners.
7. References (starting points)
IETF RATS: Working Group ·
RFC 9334 ·
RFC 9335
Trusted Computing Group: TCG
NIST Platform Firmware Resiliency: SP 800-193
EU context: Cyber Resilience Act (European Commission), ENISA overview