Cross-Domain Adversarial Inference

Mechanism

The primitive operates as a continuous coherence monitor over three nominally-independent channels. The sensor channel reports what the system's perceptual stack believes the world to be. The policy channel reports what the system's intent and action stack believes the system itself is doing. The environment channel reports what independent corroborating sources — co-operative peers, infrastructure beacons, broadcast policy artefacts, prior-state continuity — report about both the world and the system. Under non-adversarial conditions the three channels agree to within bounded tolerance. Under adversarial conditions one channel is being manipulated and the manipulation manifests as a coherence breach with the other two.

The coherence check is structured as a pairwise consistency test between channels, with a fusion step that identifies which channel is most likely to be the perturbed one. Sensor-versus-policy consistency tests whether the perceived world admits the action the system is taking; sensor-versus-environment consistency tests whether the perceived world matches what corroborating sources report; policy-versus-environment consistency tests whether the action the system is taking is admissible under the policy artefacts the environment broadcasts. A breach in any single pair raises a contradiction signal; a breach in two pairs, sharing a common channel, identifies that common channel as the probable adversarial vector.

Contradiction signals are not handled symmetrically. A sensor-channel contradiction triggers a downgrade in the perceptual confidence floor, restricting the policy to actions that can be committed under the reduced perceptual reliability. A policy-channel contradiction triggers a downgrade in the intent-tier, restricting the system to lower-commitment actions until intent can be re-corroborated. An environment-channel contradiction triggers a rejection of the environment artefact and a fall-back to the most recent corroborated environment state. The downgrade is graduated rather than binary: a small contradiction reduces operating tier modestly; a large or persistent contradiction reduces it substantially or to the rejection floor.

The fusion step is configurable per domain. In civilian operating contexts, where adversarial input is rare and operator confusion is common, the fusion is biased toward downgrade rather than rejection so that benign confusion does not produce hard failures. In defense and homeland-security contexts, where adversarial input is the design assumption, the fusion is biased toward rejection and the residual operation continues only on channels whose coherence is positively established. The mechanism is invariant across these configurations; only the fusion bias changes.

Operating Parameters

The primitive operates with a small set of explicit parameters: per-pair tolerance bounds, fusion bias, contradiction-persistence horizon, and the credential under which downgrade and rejection actions are themselves authorised. Tolerance bounds are set per channel pair and per operating context; they are wide enough to accommodate ordinary noise and narrow enough to surface material divergence. Fusion bias is set per deployment, ranging from heavily-downgrade-biased in civilian contexts to heavily-reject-biased in adversarial contexts.

The contradiction-persistence horizon distinguishes transient breaches from sustained ones. A single-frame divergence that resolves within the horizon is recorded but does not trigger downgrade; a divergence that persists beyond the horizon triggers downgrade at a magnitude proportional to the duration. This parameter prevents single-frame sensor glitches and momentary policy oscillations from cascading into spurious downgrades while preserving sensitivity to genuine, sustained adversarial input.

Credentialing applies at two layers. The classification of an input as adversarial is itself a credentialed observation: the system records, for each downgrade or rejection, the channels that breached, the magnitude and duration of the breach, and the configuration parameters that produced the determination. The action taken on the classification — the specific downgrade target, the specific fall-back environment state — is authorised under the credential governing the deployment, and a deployment that wishes to take stronger or weaker action than the default must present a credential that authorises the variation. This structure prevents both over-aggressive rejection in civilian contexts and under-aggressive downgrade in adversarial ones.

Alternative Embodiments

The primitive admits embodiments differing in the source of each channel and in the locus of the coherence check. In a vehicular embodiment the sensor channel is the on-board perception stack, the policy channel is the planner's published intent, and the environment channel is the V2X broadcast plus infrastructure-published policy and any co-operative peer's published intent. In a robotic-fleet embodiment the sensor channel is the fleet's pooled perception, the policy channel is each robot's published action, and the environment channel is the fleet supervisor's published policy and the workspace's instrumented state. In a defense-ISR embodiment the sensor channel is the platform's organic sensors, the policy channel is the platform's tasked mission, and the environment channel is the higher-echelon common operating picture and the mission-ROE artefact.

The coherence check itself admits two principal embodiments. In the centralised embodiment, the three channels are routed to a single coherence monitor that performs the pairwise tests and the fusion step; this embodiment is appropriate where the monitor can be trusted and where the channels can be aggregated with bounded latency. In the distributed embodiment, each pair of channels is monitored at the platform that holds both, and the per-pair contradiction signals are themselves fused at a higher layer; this embodiment is appropriate where the channels cannot be aggregated centrally or where the central monitor would be a single point of compromise.

The downgrade response admits embodiments ranging from a simple confidence-floor reduction (the policy continues to operate but at a reduced commit ceiling) through a tier-step demotion (the policy steps down a defined tier ladder until corroboration is restored) to a hard fall-back (the system reverts to a corroborated previous state and refuses further commitment until a higher authority intervenes). The choice is governed by domain and by the operating tier; all three embodiments preserve the credentialed-recording discipline.

Composition

The primitive composes with the operator-intent stack upstream and with the actuation stack downstream. Upstream, the intent stack provides the policy channel and consumes the contradiction signal: when contradiction is reported the intent stack reduces its own commit ceiling and may switch from one intent inference mode to another (for example, from a high-tier model that assumes co-operative environment to a low-tier model that assumes adversarial environment). Downstream, the actuation stack consumes the resulting tier and gates its commits accordingly; the composition with the reversibility classifier is direct, because a downgrade in operating tier maps directly to a tightening of the irreversible-tier authority requirement.

Laterally, the primitive composes with the evidentiary record and with the credentialed-governance flow. Each contradiction is recorded with full provenance, and the records are the substrate from which tolerance bounds and fusion biases are tuned over time. A deployment that observes systematic false-positive contradictions in benign conditions can present the record under credentialed governance and obtain a tolerance update; a deployment that observes false-negative contradictions in adversarial conditions can obtain a tightening. The mechanism is the same in both directions; the credential and the evidence are the only differences.

The primitive also composes across deployments. Contradictions observed in one deployment can, under appropriate credentialed sharing, inform the configuration of other deployments operating in similar conditions. A defence deployment that detects a novel adversarial pattern in its environment channel can publish the pattern signature under credentialed dissemination, and civilian and homeland-security deployments operating in adjacent conditions can update their tolerance bounds accordingly. The cross-deployment composition does not require the underlying observations to be shared; only the derived signatures and the tolerance updates flow.

Domain Configuration and Credential Chains

Although the mechanism is invariant across domains, the parameters under which the mechanism operates are not, and the disclosure is explicit about how those parameters are sourced. In civilian autonomous-vehicle operation the tolerance bounds are wide, the fusion bias is downgrade-favouring, the contradiction-persistence horizon is set to absorb the kinds of transient breaches that ordinary urban driving produces, and the credential chain runs through a transport-regulatory authority that signs the deployment-level configuration. In commercial-fleet operation the parameters are tightened modestly to support actuarial-grade safety analysis, and the credential chain runs through the fleet operator's regulatory framework. In emergency-response operation the parameters are tuned to the multi-agency dispatch context, where the environment channel includes dispatcher-published artefacts, and the credential chain runs through the responsible jurisdiction.

In defence ISR the parameters are at the rejection-favouring end of the range, the contradiction-persistence horizon is short so that adversarial perturbations are surfaced quickly, and the credential chain runs through national command authority via theatre command via mission rules of engagement. In homeland-security applications the parameters are tuned to the specific adversarial-detection role, with credential chains that run through the appropriate civilian-security authority. In each of these domains the same primitive operates; only the parameters and the credential chain differ. This invariance is what makes the primitive useful as a cross-domain disclosure: an organisation operating across multiple domains can deploy a single implementation and configure it per deployment, rather than building a separate adversarial-inference stack per domain.

The disclosure is explicit that the configuration parameters and the credential chain are themselves part of the protected scope only in their structural relationship. The specific numerical tolerances, the specific fusion bias values, and the specific authorities are deployment-dependent and are not themselves the subject of the claim; the claim is to the structure that admits any of them under appropriate credential.

Prior-Art Distinction

Existing adversarial-input handling in autonomous systems is dominated by two approaches. The first is per-channel hardening: each channel is made robust to its own characteristic attacks (sensor spoofing is countered by sensor-level cryptography or sensor-level statistical detectors; policy injection is countered by policy-channel signatures; environment spoofing is countered by environment-channel signatures). The second is end-to-end adversarial training: the system is trained against representative adversarial inputs and is expected to reject them on the basis of learned discriminators.

The primitive described here differs from both. It does not assume that any single channel can be made unconditionally robust, and it does not rely on the system having seen the specific adversarial pattern in training. It detects adversarial input by the structural fact that adversarial input perturbs one channel in ways the other channels do not corroborate, and it responds with a graduated downgrade or rejection that is itself credentialed and recorded. The combination — cross-channel coherence, identification of the probable adversarial channel by pairwise breach pattern, graduated and credentialed response, and cross-deployment signature dissemination — is not present in the per-channel-hardening literature and is not present in the adversarial-training literature.

Disclosure Scope

The disclosure covers the cross-channel coherence mechanism, the pairwise breach pattern that identifies the probable adversarial channel, the graduated-downgrade and rejection-fall-back response disciplines, the credentialed recording and credentialed action authorities that govern those responses, and the cross-deployment signature dissemination flow. It covers the embodiments above and any embodiment that preserves these disciplines together. It does not cover any embodiment that responds to single-channel anomalies without cross-channel corroboration, that takes downgrade or rejection action without credentialed authorisation, or that disseminates raw cross-deployment observations rather than derived signatures.