Mechanisms · category

Remote & side-channel sensing

Inferring activity from outside or from physical signals: detecting data centres, classifying workloads from power or other emissions.

Name	Type	Readiness	Verifies	Threat model
On-chip telemetry from timing, memory and performance counters Uses timing, memory-residency and performance-counter signals measured on AI accelerators as evidence about which workloads they are running. ⚠ Open critical flaw	Mechanism	R2Demonstrated	This compute runs inference, not training Declared hardware is idle or shut down There is no undeclared relevant compute A training run stayed within declared limits	Semi-trusted prover
Workload classification from telemetry and side channels Telling whether chips are training, serving or doing non-AI work from GPU counters or power draw, signals that do not read weights or data.	Mechanism	R2Demonstrated	This compute runs inference, not training A training run stayed within declared limits	Adversarial prover
Remote detection of data centres Remote detection locates large data centres and estimates their power capacity without site access, using satellite imagery, heat signatures and public records such as permits.	Mechanism	R1Proposed	There is no undeclared relevant compute Compute stock is at most a declared amount	Adversarial prover

Includes records that list this as a secondary category. Claims in grey italics are supported rather than aimed at.